Journal articles on the topic 'GAMLSS (generalized additive models for location, scale and shape) statistics'
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Stasinopoulos, Mikis D., Robert A. Rigby, and Fernanda De Bastiani. "GAMLSS: A distributional regression approach." Statistical Modelling 18, no. 3-4 (March 29, 2018): 248–73. http://dx.doi.org/10.1177/1471082x18759144.
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Abstract: A tutorial of the generalized additive models for location, scale and shape (GAMLSS) is given here using two examples. GAMLSS is a general framework for performing regression analysis where not only the location (e.g., the mean) of the distribution but also the scale and shape of the distribution can be modelled by explanatory variables.
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Mayr, Andreas, Matthias Schmid, Annette Pfahlberg, Wolfgang Uter, and Olaf Gefeller. "A permutation test to analyse systematic bias and random measurement errors of medical devices via boosting location and scale models." Statistical Methods in Medical Research 26, no. 3 (April 24, 2015): 1443–60. http://dx.doi.org/10.1177/0962280215581855.
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Measurement errors of medico-technical devices can be separated into systematic bias and random error. We propose a new method to address both simultaneously via generalized additive models for location, scale and shape (GAMLSS) in combination with permutation tests. More precisely, we extend a recently proposed boosting algorithm for GAMLSS to provide a test procedure to analyse potential device effects on the measurements. We carried out a large-scale simulation study to provide empirical evidence that our method is able to identify possible sources of systematic bias as well as random error under different conditions. Finally, we apply our approach to compare measurements of skin pigmentation from two different devices in an epidemiological study.
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Xiong, Lihua, Cong Jiang, and Tao Du. "Statistical attribution analysis of the nonstationarity of the annual runoff series of the Weihe River." Water Science and Technology 70, no. 5 (July 21, 2014): 939–46. http://dx.doi.org/10.2166/wst.2014.322.
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Time-varying moments models based on Pearson Type III and normal distributions respectively are built under the generalized additive model in location, scale and shape (GAMLSS) framework to analyze the nonstationarity of the annual runoff series of the Weihe River, the largest tributary of the Yellow River. The detection of nonstationarities in hydrological time series (annual runoff, precipitation and temperature) from 1960 to 2009 is carried out using a GAMLSS model, and then the covariate analysis for the annual runoff series is implemented with GAMLSS. Finally, the attribution of each covariate to the nonstationarity of annual runoff is analyzed quantitatively. The results demonstrate that (1) obvious change-points exist in all three hydrological series, (2) precipitation, temperature and irrigated area are all significant covariates of the annual runoff series, and (3) temperature increase plays the main role in leading to the reduction of the annual runoff series in the study basin, followed by the decrease of precipitation and the increase of irrigated area.
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Greven, Sonja, and Fabian Scheipl. "A general framework for functional regression modelling." Statistical Modelling 17, no. 1-2 (February 2017): 1–35. http://dx.doi.org/10.1177/1471082x16681317.
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Researchers are increasingly interested in regression models for functional data. This article discusses a comprehensive framework for additive (mixed) models for functional responses and/or functional covariates based on the guiding principle of reframing functional regression in terms of corresponding models for scalar data, allowing the adaptation of a large body of existing methods for these novel tasks. The framework encompasses many existing as well as new models. It includes regression for ‘generalized’ functional data, mean regression, quantile regression as well as generalized additive models for location, shape and scale (GAMLSS) for functional data. It admits many flexible linear, smooth or interaction terms of scalar and functional covariates as well as (functional) random effects and allows flexible choices of bases—particularly splines and functional principal components—and corresponding penalties for each term. It covers functional data observed on common (dense) or curve-specific (sparse) grids. Penalized-likelihood-based and gradient-boosting-based inference for these models are implemented in R packages refund and FDboost , respectively. We also discuss identifiability and computational complexity for the functional regression models covered. A running example on a longitudinal multiple sclerosis imaging study serves to illustrate the flexibility and utility of the proposed model class. Reproducible code for this case study is made available online.
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Berger, Moritz, and Matthias Schmid. "Flexible modeling of ratio outcomes in clinical and epidemiological research." Statistical Methods in Medical Research 29, no. 8 (December 9, 2019): 2250–68. http://dx.doi.org/10.1177/0962280219891195.
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In medical studies one frequently encounters ratio outcomes. For modeling these right-skewed positive variables, two approaches are in common use. The first one assumes that the outcome follows a normal distribution after transformation (e.g. a log-normal distribution), and the second one assumes gamma distributed outcome values. Classical regression approaches relate the mean ratio to a set of explanatory variables and treat the other parameters of the underlying distribution as nuisance parameters. Here, more flexible extensions for modeling ratio outcomes are proposed that allow to relate all the distribution parameters to explanatory variables. The models are embedded into the framework of generalized additive models for location, scale and shape (GAMLSS), and can be fitted using a component-wise gradient boosting algorithm. The added value of the new modeling approach is demonstrated by the analysis of the LDL/HDL cholesterol ratio, which is a strong predictor of cardiovascular events, using data from the German Chronic Kidney Disease Study. Particularly, our results confirm various important findings on risk factors for cardiovascular events.
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Oliveira, Tiago Almeida, Sílvio Fernando Alves Xavier Júnior, Gláucia Amorim Faria, Beatriz Garcia Lopes, Ednário Mendonça Barbosa, and Ana Patrícia Bastos Peixoto. "An Application of Generalized Additive Models of Location, Scale, and Shape (GAMLSS) to estimate the Eucalyptus Height." Ciência e Natura 42 (May 13, 2020): e15. http://dx.doi.org/10.5902/2179460x41710.
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The Generalized Additive Models for Location, Scale, and Shape (GAMLSS) are a recent class of models that further flexibilitythe distribution of the response variable. The regression analysis has been used to model biological phenomena, and its variousmodalities have met the need for its use with precision. However, there are situations in which the adjustment of models with moreflexible assumptions in the specification of the distribution of the response variable becomes indispensable, thus justifying the useof GAMLSS. The study of plant growth curves has full application in agricultural research; thus, it is crucial to know the habits ofgrowth and development of forest species is crucial for reforestation programs and in the most diverse researches. The study aimedto model the growth of Eucalyptus through the adjusting of Generalized Additive Models for Location, Scale, and Shape, in orderto promote improvements on crop productivity. Considering all parameters of the independent variable (time) under GAMLSSclass modeling, the distribution model ST3 presented better results.
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Roquim, Fernanda V., Thiago G. Ramires, Luiz R. Nakamura, Ana J. Righetto, Renato R. Lima, and Rayne A. Gomes. "Building flexible regression models: including the Birnbaum-Saunders distribution in the gamlss package." Semina: Ciências Exatas e Tecnológicas 42, no. 2 (November 3, 2021): 163. http://dx.doi.org/10.5433/1679-0375.2021v42n2p163.
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Generalized additive models for location, scale and shape (GAMLSS) are a very flexible statistical modeling framework, being an important generalization of the well-known generalized linear models and generalized additive models. Their main advantage is that any probability distribution (that does not necessarily belong to the exponential family) can be considered to model the response variable and different regression structures can be fitted in each of its parameters. Currently, there are more than 100 distributions that are already implemented in the gamlss package in R software. Nevertheless, researchers can implement different distributions if they are not yet available, e.g., the Birnbaum-Saunders (BS) distribution, which is widely used in fatigue studies. In this paper we make available all codes regarding the inclusion of the BS distribution in the gamlss package, and then present a simple application related to air quality data for illustration purposes
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Ramires, Thiago G., Luiz R. Nakamura, Ana J. Righetto, Renan J. Carvalho, Lucas A. Vieira, and Carlos A. B. Pereira. "Comparison between Highly Complex Location Models and GAMLSS." Entropy 23, no. 4 (April 16, 2021): 469. http://dx.doi.org/10.3390/e23040469.
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This paper presents a discussion regarding regression models, especially those belonging to the location class. Our main motivation is that, with simple distributions having simple interpretations, in some cases, one gets better results than the ones obtained with overly complex distributions. For instance, with the reverse Gumbel (RG) distribution, it is possible to explain response variables by making use of the generalized additive models for location, scale, and shape (GAMLSS) framework, which allows the fitting of several parameters (characteristics) of the probabilistic distributions, like mean, mode, variance, and others. Three real data applications are used to compare several location models against the RG under the GAMLSS framework. The intention is to show that the use of a simple distribution (e.g., RG) based on a more sophisticated regression structure may be preferable than using a more complex location model.
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Sá, Ana C. L., Maria A. A. Turkman, and José M. C. Pereira. "Exploring fire incidence in Portugal using generalized additive models for location, scale and shape (GAMLSS)." Modeling Earth Systems and Environment 4, no. 1 (January 16, 2018): 199–220. http://dx.doi.org/10.1007/s40808-017-0409-6.
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Barajas, Freddy Hernández, Mabel Torres, Lina Arteaga, and Cristina Castro. "GAMLSS models applied in the treatment of agro-industrial waste." Comunicaciones en Estadística 8, no. 2 (December 30, 2015): 245. http://dx.doi.org/10.15332/s2027-3355.2015.0002.07.
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In this paper, we present an application of GAMLSS (Generalized Additive Models for Location, Shape and Scale) to study bacterial cellulose production from agro-industrial waste. An experiment was conducted to research the effects of pH and cultivation time on bacterial cellulose yield obtained from discarded bananas. Several models were fitted to the collected data to determine an estimated expression for the mean and variance of bacterial cellulose yield. We found that the mean and variance of cellulose yield decrease as pH increases, while the opposite occurs as cultivation time increases.
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Boucher, Jean-Philippe, and Roxane Turcotte. "A Longitudinal Analysis of the Impact of Distance Driven on the Probability of Car Accidents." Risks 8, no. 3 (September 1, 2020): 91. http://dx.doi.org/10.3390/risks8030091.
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Using telematics data, we study the relationship between claim frequency and distance driven through different models by observing smooth functions. We used Generalized Additive Models (GAM) for a Poisson distribution, and Generalized Additive Models for Location, Scale, and Shape (GAMLSS) that we generalize for panel count data. To correctly observe the relationship between distance driven and claim frequency, we show that a Poisson distribution with fixed effects should be used because it removes residual heterogeneity that was incorrectly captured by previous models based on GAM and GAMLSS theory. We show that an approximately linear relationship between distance driven and claim frequency can be derived. We argue that this approach can be used to compute the premium surcharge for additional kilometers the insured wants to drive, or as the basis to construct Pay-as-you-drive (PAYD) insurance for self-service vehicles. All models are illustrated using data from a major Canadian insurance company.
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Rigby, R. A., and D. M. Stasinopoulos. "Generalized additive models for location, scale and shape (with discussion)." Journal of the Royal Statistical Society: Series C (Applied Statistics) 54, no. 3 (June 2005): 507–54. http://dx.doi.org/10.1111/j.1467-9876.2005.00510.x.
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Ramires, Thiago G., Luiz R. Nakamura, Ana J. Righetto, Andréa C. Konrath, and Carlos A. B. Pereira. "Incorporating Clustering Techniques into GAMLSS." Stats 4, no. 4 (November 12, 2021): 916–30. http://dx.doi.org/10.3390/stats4040053.
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A method for statistical analysis of multimodal and/or highly distorted data is presented. The new methodology combines different clustering methods with the GAMLSS (generalized additive models for location, scale, and shape) framework, and is therefore called c-GAMLSS, for “clustering GAMLSS. ” In this new extended structure, a latent variable (cluster) is created to explain the response-variable (target). Any and all parameters of the distribution for the response variable can also be modeled by functions of the new covariate added to other available resources (features). The method of selecting resources to be used is carried out in stages, a step-based method. A simulation study considering multiple scenarios is presented to compare the c-GAMLSS method with existing Gaussian mixture models. We show by means of four different data applications that in cases where other authentic explanatory variables are or are not available, the c-GAMLSS structure outperforms mixture models, some recently developed complex distributions, cluster-weighted models, and a mixture-of-experts model. Even though we use simple distributions in our examples, other more sophisticated distributions can be used to explain the response variable.
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Fathurahman, M., Ika Purnamasari, and Surya Prangga. "COUNT DATA MODELING USING GAMLSS APPROACH AND ITS APPLICATION IN DENGUE HEMORRHAGIC FEVER CASES IN EAST KALIMANTAN PROVINCE, INDONESIA." Journal of Southwest Jiaotong University 56, no. 6 (December 24, 2021): 1012–19. http://dx.doi.org/10.35741/issn.0258-2724.56.6.88.
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Generalized Additive Models for Location, Scale, and Shape (GAMLSS) is a robust approach used to model various types and characteristics of data. Therefore, this research aims to model the count data using the GAMLSS approach through Poisson Regression (PR), Poisson Inverse Gaussian Regression (PIGR), and Negative Binomial Regression (NBR). PIGR and NBR are the best models compared to PR based on their application to modeling the number of dengue hemorrhagic fever (DHF) cases in East Kalimantan Province, Indonesia, in 2019. Furthermore, both models produced varying results on the factors with a significant effect on DHF. Only one factor of the PIGR model, namely altitude, significantly affected these cases. Meanwhile, the NBR model produced three factors that affected the number of dengue cases: altitude, population density, and health workers.
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Dantas, Leydson G., Carlos A. C. dos Santos, Ricardo A. de Olinda, José I. B. de Brito, Celso A. G. Santos, Eduardo S. P. R. Martins, Gabriel de Oliveira, and Nathaniel A. Brunsell. "Rainfall Prediction in the State of Paraíba, Northeastern Brazil Using Generalized Additive Models." Water 12, no. 9 (September 4, 2020): 2478. http://dx.doi.org/10.3390/w12092478.
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The state of Paraíba is part of the semi-arid region of Brazil, where severe droughts have occurred in recent years, resulting in significant socio-economic losses associated with climate variability. Thus, understanding to what extent precipitation can be influenced by sea surface temperature (SST) patterns in the tropical region can help, along with a monitoring system, to set up an early warning system, the first pillar in drought management. In this study, Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used to filter climatic indices with higher predictive efficiency and, as a result, to perform rainfall predictions. The results show the persistent influence of tropical SST patterns in Paraíba rainfall, the tropical Atlantic Ocean impacting the rainfall distribution more effectively than the tropical Pacific Ocean. The GAMLSS model showed predictive capability during summer and southern autumn in Paraíba, highlighting the JFM (January, February and March), FMA (February, March and April), MAM (March, April and May), and AMJ (April, May and June) trimesters as those with the highest predictive potential. The methodology demonstrates the ability to be integrated with regional forecasting models (ensemble). Such information has the potential to inform decisions in multiple sectors, such as agriculture and water resources, aiming at the sustainable management of water resources and resilience to climate risk.
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Voncken, Lieke, Casper J. Albers, and Marieke E. Timmerman. "Model Selection in Continuous Test Norming With GAMLSS." Assessment 26, no. 7 (June 29, 2017): 1329–46. http://dx.doi.org/10.1177/1073191117715113.
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To compute norms from reference group test scores, continuous norming is preferred over traditional norming. A suitable continuous norming approach for continuous data is the use of the Box–Cox Power Exponential model, which is found in the generalized additive models for location, scale, and shape. Applying the Box–Cox Power Exponential model for test norming requires model selection, but it is unknown how well this can be done with an automatic selection procedure. In a simulation study, we compared the performance of two stepwise model selection procedures combined with four model-fit criteria (Akaike information criterion, Bayesian information criterion, generalized Akaike information criterion (3), cross-validation), varying data complexity, sampling design, and sample size in a fully crossed design. The new procedure combined with one of the generalized Akaike information criterion was the most efficient model selection procedure (i.e., required the smallest sample size). The advocated model selection procedure is illustrated with norming data of an intelligence test.
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Wahyuni, Silvia Tri, Tiani Wahyu Utami, and Moh Yamin Darsyah. "Pemodelan Generalized Additive Model For Location, Scale, and Shape (Gamlss) Dengan Pemulusan Locally Estimated Scatterplot Smoothing (Loess) pada Kasus Hiv/Aids Di Jawa Timur." Jurnal Litbang Edusaintech 2, no. 1 (May 31, 2021): 18–26. http://dx.doi.org/10.51402/jle.v2i1.7.
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HIV / AIDS is a contagious disease that can attack all age groups of the population and is a health challenge in almost all over the world including Indonesia. Therefore, it is necessary to model HIV / AIDS cases for the factors that are suspected to influence them. One suitable method for estimating factors that influence HIV / AIDS is the Generalized Additive Model for Location, Scale, and Shape (GAMLSS). The GAMLSS method is flexible because it includes expansion of a good exponential family distribution to handle overdispersion data, continuous data, and discrete data. This research will apply GAMLSS semiparametric modeling with LOESS smoothing to find out the characteristics and models of HIV / AIDS cases in East Java in 2017. Based on the analysis, it was found that the variables that significantly affected were the number of homeless people, number of victims of drug abuse, population poor, and the number of fertile age couples using condom contraception with AIC value of 437,404, degree = 1 and span = 0.3, and the distribution used is Negative Binomial I.
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Ganegoda, Amandha, and John Evans. "A scaling model for severity of operational losses using generalized additive models for location scale and shape (GAMLSS)." Annals of Actuarial Science 7, no. 1 (October 30, 2012): 61–100. http://dx.doi.org/10.1017/s1748499512000267.
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AbstractIn this paper, we investigate the problem of how to combine operational losses collected from various banks of different sizes and loss reporting thresholds in order to estimate the distribution of operational loss severities for a bank of a given size. We model the severity of operational losses by using the extreme value theory to account for the reporting bias of the external data, and a regression analysis based on the GAMLSS framework to model the scaling properties of operational losses. In contrast to previous studies on the scaling problem, our analysis gives particular emphasis to the scaling properties of the tail of the loss distribution. Contrary to existing knowledge, we find that the size of a bank is an important determinant of the severity of operational losses and that the tail index of the distribution is negatively correlated with the size of the bank. The results indicate that for very large banks, distribution of the operational loss severity can be extremely heavy tailed (i.e. tail index less than 1), a finding which have significant implications for capital calculation as well as for risk management. Furthermore, we also demonstrate that the capital estimates provided by our model is consistent with the industry standards and the model can be used by individual banks to simulate data to complement their internal data.
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Ötting, Marius, Roland Langrock, and Christian Deutscher. "Integrating multiple data sources in match-fixing warning systems." Statistical Modelling 18, no. 5-6 (November 18, 2018): 483–504. http://dx.doi.org/10.1177/1471082x18804933.
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Recent years have seen several match-fixing scandals in soccer. In order to avoid match-fixing, existing literature and fraud detection systems primarily focus on analysing betting odds provided by bookmakers. In our work, we suggest to not only analyse odds but also total volume placed on bets, thereby making use of more of the information available. As a case study for our method, we consider the second division in Italian soccer, Serie B, since for this league it has effectively been proven that some matches were fixed, such that to some extent we can ground truth our approach. For the betting volume data, we use a flexible generalized additive model for location, scale and shape (GAMLSS), with log-normal response, to account for the various complex patterns present in the data. For the betting odds, we use a GAMLSS with bivariate Poisson response to model the number of goals scored by both teams, and to subsequently derive the corresponding odds. We then conduct outlier detection in order to flag suspicious matches. Our results indicate that monitoring both betting volumes and betting odds can lead to more reliable detection of suspicious matches.
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Fantazzini, Tatiana Botelho, Sttela Dellyzete Veiga Franco da Rosa, Gladyston Rodrigues Carvalho, Gilberto Rodrigues Liska, Maria Laene Moreira de Carvalho, Stefânia Vilas Boas Coelho, Marcelo Ângelo Cirillo, and Fernando Augusto Sales Ribeiro. "Correlation between historical data of the germination test and of the tetrazolium test in coffee seeds by GAMLSS." Seed Science and Technology 48, no. 2 (August 31, 2020): 179–88. http://dx.doi.org/10.15258/sst.2020.48.2.05.
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In the Brazilian National System of Seeds and Seedlings, coffee seeds are evaluated by the germination or tetrazolium test. However, differences have been observed between the results of these tests in various studies, especially when the seeds have a lower level of quality. Given this situation, the aim of this study was to evaluate the correlation between historical data of results of the germination test and of the tetrazolium test in samples of coffee seeds using Generalized Additive Models for Location, Scale and Shape (GAMLSS). Historical data of results of the germination test and of the tetrazolium test of coffee seeds originating from different cultivars and different crop seasons were used. The zero-or-one inflated beta GAMLSS is suitable for fitting data from the germination test and from the tetrazolium test. The estimate of viability by the tetrazolium test varies according to the germination percentage class. There are greater GAMLSS correlations between the percentages of normal seedlings and of viability in the tetrazolium test for germination values above 70%, and low correlations below this value, showing that evaluation of coffee seeds based only on the tetrazolium test may not correspond to actual physiological performance.
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Qu, Chunlai, Jing Li, Lei Yan, Pengtao Yan, Fang Cheng, and Dongyang Lu. "Non-Stationary Flood Frequency Analysis Using Cubic B-Spline-Based GAMLSS Model." Water 12, no. 7 (June 29, 2020): 1867. http://dx.doi.org/10.3390/w12071867.
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Under changing environments, the most widely used non-stationary flood frequency analysis (NFFA) method is the generalized additive models for location, scale and shape (GAMLSS) model. However, the model structure of the GAMLSS model is relatively complex due to the large number of statistical parameters, and the relationship between statistical parameters and covariates is assumed to be unchanged in future, which may be unreasonable. In recent years, nonparametric methods have received increasing attention in the field of NFFA. Among them, the linear quantile regression (QR-L) model and the non-linear quantile regression model of cubic B-spline (QR-CB) have been introduced into NFFA studies because they do not need to determine statistical parameters and consider the relationship between statistical parameters and covariates. However, these two quantile regression models have difficulties in estimating non-stationary design flood, since the trend of the established model must be extrapolated infinitely to estimate design flood. Besides, the number of available observations becomes scarcer when estimating design values corresponding to higher return periods, leading to unreasonable and inaccurate design values. In this study, we attempt to propose a cubic B-spline-based GAMLSS model (GAMLSS-CB) for NFFA. In the GAMLSS-CB model, the relationship between statistical parameters and covariates is fitted by the cubic B-spline under the GAMLSS model framework. We also compare the performance of different non-stationary models, namely the QR-L, QR-CB, and GAMLSS-CB models. Finally, based on the optimal non-stationary model, the non-stationary design flood values are estimated using the average design life level method (ADLL). The annual maximum flood series of four stations in the Weihe River basin and the Pearl River basin are taken as examples. The results show that the GAMLSS-CB model displays the best model performance compared with the QR-L and QR-CB models. Moreover, it is feasible to estimate design flood values based on the GAMLSS-CB model using the ADLL method, while the estimation of design flood based on the quantile regression model requires further studies.
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Klein, Nadja, Michel Denuit, Stefan Lang, and Thomas Kneib. "Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape." Insurance: Mathematics and Economics 55 (March 2014): 225–49. http://dx.doi.org/10.1016/j.insmatheco.2014.02.001.
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Klein, Nadja, Thomas Kneib, and Stefan Lang. "Bayesian Generalized Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data." Journal of the American Statistical Association 110, no. 509 (January 2, 2015): 405–19. http://dx.doi.org/10.1080/01621459.2014.912955.
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Cajias, Marcelo. "Is there room for another hedonic model?" Journal of European Real Estate Research 11, no. 2 (August 6, 2018): 204–45. http://dx.doi.org/10.1108/jerer-07-2017-0025.
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Purpose This paper aims to explore the in-sample explanatory and out-of-sample forecasting accuracy of the generalized additive model for location, scale and shape (GAMLSS) model in contrast to the GAM method in Munich’s residential market. Design/methodology/approach The paper explores the in-sample explanatory results via comparison of coefficients and a graphical analysis of non-linear effects. The out-of-sample forecasting accuracy focusses on 50 loops of three models excluding 10 per cent of the observations randomly. Afterwards, it obtains the predicted functional forms and predicts the remaining 10 per cent. The forecasting performance is measured via error variance, root mean squared error, mean absolute error and the mean percentage error. Findings The results show that the complexity of asking rents in Munich is more accurately captured by the GAMLSS approach than the GAM as shown by an outperformance in the in-sample explanatory accuracy. The results further show that the theoretical and empirical complexities do pay off in view of the increased out-of-sample forecasting power of the GAMLSS approach. Research limitations/implications The computational requirements necessary to estimate GAMLSS models in terms of number of cores and RAM are high and might constitute one of the limiting factors for (institutional) researchers. Moreover, large and detailed knowledge on statistical inference and programming is necessary. Practical implications The usage of the GAMLSS approach would lead policymakers to better understand the local factors affecting rents. Institutional researchers, instead, would clearly aim at calibrating the forecasting accuracy of the model to better forecast rents in investment strategies. Finally, future researchers are encouraged to exploit the large potential of the GAMLSS framework and its modelling flexibility. Originality/value The GAMLSS approach is widely recognised and used by international institutions such as the World Health Organisation, the International Monetary Fund and the European Commission. This is the first study to the best of the author’s knowledge to assess the properties of the GAMLSS approach in applied real estate research from a statistical asymptotic perspective by using a unique data basis with more than 38,000 observations.
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Wu, Dian, Hyeon-Cheol Yoon, Joo-Heon Lee, and Jong-Suk Kim. "Regional Analysis of Hotspot and Coldspot Areas Undergoing Nonstationary Drought Characteristics in a Changing Climate." Applied Sciences 12, no. 17 (August 25, 2022): 8479. http://dx.doi.org/10.3390/app12178479.
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Conventional drought indices based on stationary assumptions are no longer appropriate for drought assessments conducted under conditions with climate change or anthropogenic influences. In this study, a time-varying Nonstationary Standardized Precipitation Index (NSPEI) was developed by fitting a time covariate with the Generalized Additive Models for Location, Scale, and Shape (GAMLSS), with a time-scale of six months. Daily precipitation, maximum temperature, and minimum temperature datasets from 1979–2020 that were based on the Climate Prediction Center (CPC) global unified gauge-based analysis with a resolution of 0.5° × 0.5° were used. The results of the study indicated that both precipitation and evapotranspiration in China had increased significantly over the past 42 years in China and that Northwest China would become drier. By extracting the return objects of the GAMLSS, this study identified Northwest China (Continental River Basin) as the main region wherein the distribution parameters of the non-stationary models changed; this region was identified as the one concentrated with nonstationary hotspot response areas. A comparison of drought duration and severity showed that the stationary SPEI under-estimated the severity of the drought. The severity was under-estimated in the spring–summer and fall–winter seasons for Northwest and Southwest of China, respectively; more attention should be paid to these regions. This study provides results that can support nonstationary drought research; droughts can be identified more precisely, and early warnings can be provided for them.
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Wojtyś, Małgorzata, Giampiero Marra, and Rosalba Radice. "Copula based generalized additive models for location, scale and shape with non-random sample selection." Computational Statistics & Data Analysis 127 (November 2018): 1–14. http://dx.doi.org/10.1016/j.csda.2018.05.001.
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Groll, Andreas, Julien Hambuckers, Thomas Kneib, and Nikolaus Umlauf. "LASSO-type penalization in the framework of generalized additive models for location, scale and shape." Computational Statistics & Data Analysis 140 (December 2019): 59–73. http://dx.doi.org/10.1016/j.csda.2019.06.005.
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He, Chaofei, Fulong Chen, Aihua Long, Chengyan Luo, and Changlu Qiao. "Frequency Analysis of Snowmelt Flood Based on GAMLSS Model in Manas River Basin, China." Water 13, no. 15 (July 22, 2021): 2007. http://dx.doi.org/10.3390/w13152007.
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With the acceleration of human economic activities and dramatic changes in climate, the validity of the stationarity assumption of flood time series frequency analysis has been questioned. In this study, a framework for flood frequency analysis is developed on the basis of a tool, namely, the Generalized Additive Models for Location, Scale, and Shape (GAMLSS). We introduced this model to construct a non-stationary model with time and climate factor as covariates for the 50-year snowmelt flood time series in the Kenswat Reservoir control basin of the Manas River. The study shows that there are clear non-stationarities in the flood regime, and the characteristic series of snowmelt flood shows an increasing trend with the passing of time. The parameters of the flood distributions are modelled as functions of climate indices (temperature and rainfall). The physical mechanism was incorporated into the study, and the simulation results are similar to the actual flood conditions, which can better describe the dynamic process of snowmelt flood characteristic series. Compared with the design flood results of Kenswat Reservoir approved by the China Renewable Energy Engineering Institute in December 2008, the design value of the GAMLSS non-stationary model considers that the impact of climate factors create a design risk in dry years by underestimating the risk.
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Jiang, Shangwen, and Ling Kang. "Flood frequency analysis for annual maximum streamflow using a non-stationary GEV model." E3S Web of Conferences 79 (2019): 03022. http://dx.doi.org/10.1051/e3sconf/20197903022.
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Under changing environment, the streamflow series in the Yangtze River have undergone great changes and it has raised widespread concerns. In this study, the annual maximum flow (AMF) series at the Yichang station were used for flood frequency analysis, in which a time varying model was constructed to account for non-stationarity. The generalized extreme value (GEV) distribution was adopted to fit the AMF series, and the Generalized Additive Models for Location, Scale and Shape (GAMLSS) framework was applied for parameter estimation. The non-stationary return period and risk of failure were calculated and compared for flood risk assessment between stationary and non-stationary models. The results demonstrated that the flow regime at the Yichang station has changed over time and a decreasing trend was detected in the AMF series. The design flood peak given a return period decreased in the non-stationary model, and the risk of failure is also smaller given a design life, which indicated a safer flood condition in the future compared with the stationary model. The conclusions in this study may contribute to long-term decision making in the Yangtze River basin under non-stationary conditions.
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Gary, Sebastian, and Wolfgang Lenhard. "In norming we trust." Diagnostica 67, no. 2 (April 2021): 75–86. http://dx.doi.org/10.1026/0012-1924/a000263.
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Zusammenfassung. Ziel der Untersuchung war ein systematischer Vergleich verschiedener Verfahren zur Normdatenmodellierung. Der auf Taylor-Polynomen basierende semi-parametrische Normierungsansatz (SPCN) mittels cNORM ( Lenhard, Lenhard & Gary, 2018 ) wurde parametrischen Anpassungen basierend auf Generalized Additive Models for Location, Scale and Shape (GAMLSS; Stasinopoulos et al., 2018 ) gegenübergestellt und die Normierungsgüte in Abhängigkeit der Faktoren Normstichprobengröße ( n = 525, 700, 1 050, 1 750), Itemanzahl (i = 10, 20, 40) sowie Itemschwierigkeit analysiert. Die Modellierung erfolgte kreuzvalidiert auf der Basis simulierter Rohdaten von Normierungs- und Validierungsstichproben: Mittels der verschiedenen Verfahren wurden auf der Basis der Normierungsstichprobe statistische Modelle berechnet und auf die Validierungsstichprobe übertragen, um die jeweils vorhergesagten mit den tatsächlichen Normwerten zu vergleichen. Der semi-parametrische Ansatz lieferte in den meisten Fällen den geringsten Normierungsfehler und damit das beste Normierungsergebnis. Die deutlichsten Unterschiede fanden sich bei leichten bzw. schweren Testskalen in Verbindung mit einer kleinen Itemanzahl. Der Einfluss der Normstichprobengröße war bei allen Methoden vergleichbar.
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Mayr, Andreas, Nora Fenske, Benjamin Hofner, Thomas Kneib, and Matthias Schmid. "Generalized additive models for location, scale and shape for high dimensional data-a flexible approach based on boosting." Journal of the Royal Statistical Society: Series C (Applied Statistics) 61, no. 3 (January 30, 2012): 403–27. http://dx.doi.org/10.1111/j.1467-9876.2011.01033.x.
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Rauhut, Alexander. "Exploring the Effect of Conversion on the Distribution of Inflectional Suffixes: A Multivariate Corpus Study." Zeitschrift für Anglistik und Amerikanistik 69, no. 3 (September 1, 2021): 267–90. http://dx.doi.org/10.1515/zaa-2021-2024.
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Abstract Lexical ambiguity in the English language is abundant. Word-class ambiguity is even inherently tied to the productive process of conversion. Most lexemes are rather flexible when it comes to word class, which is facilitated by the minimal morphology that English has preserved. This study takes a multivariate quantitative approach to examine potential patterns that arise in a lexicon where verb-noun and noun-verb conversion are pervasive. The distributions of three inflectional suffixes, verbal -s, nominal -s, and -ed are explored for their interaction with degrees of verb-noun conversion. In order to achieve that, the lexical dispersion, context-dependency, and lexical similarity between the inflected and bare forms were taken into consideration and controlled for in a Generalized Additive Models for Location, Scale and Shape (GAMLSS; Stasinopoulos, M. D., R. A. Rigby, and F. De Bastiani. 2018. “GAMLSS: A Distributional Regression Approach.” Statistical Modelling 18 (3–4): 248–73). The results of a series of zero-one-inflated beta models suggest that there is a clear “uncanny” valley of lexemes that show similar proportions of verbal and nominal uses. Such lexemes have a lower proportion of inflectional uses when textual dispersion and context-dependency are controlled for. Furthermore, as soon as there is some degree of conversion, the probability that a lexeme is always encountered without inflection sharply rises. Disambiguation by means of inflection is unlikely to play a uniform role depending on the inflectional distribution of a lexeme.
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Costa, Álefe Chagas de Lima, Antonio Dennys Melo de Oliveira, João Pedro Soares Caraciolo, Leandro Ricardo Rodrigues de Lucena, and Maurício Luiz de Mello Vieira Leite. "A GAMLSS approach to predicting growth of Nopalea cochenillifera Giant Sweet clone submitted to water and saline stress." Acta Scientiarum. Agronomy 44 (May 24, 2022): e54939. http://dx.doi.org/10.4025/actasciagron.v44i1.54939.
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Water and saline stresses are the main factors affecting agricultural production in semiarid regions. The tolerance of forage cactus to water and salt deficit makes it a promising solution, in particular Nopalea cochenillifera. The growth curves for species facing these conditions can provide useful information supporting the cultivation and management of natural populations and carry significant biological importance as growth rate assessment contributes to maintaining species viability. The objective of this study was to estimate the plant height and linear dimensions (length, width, and thickness) of N. cochenillifera Giant Sweet clone growing under water and saline stress. The experiment design was completely randomized, comprising a 4 × 4 factorial, with four water and four salinity levels; there were four replications. In order to estimate plant height in N. cochenillifera Giant Sweet clone as a function of the accumulated thermal sum, generalized additive models for location, scale, and shape (GAMLSS) were used to determine water level, saline level, length, width, and thickness. We constructed models using four distributions: the Weibull, Gumbel, Logistic, and Box-Cox power exponential distributions. The models were evaluated using global deviation and the generalized Akaike criterion. The Box–Cox power exponential proved to be the most effective in estimating N. cochenillifera height. This model enabled information relevant to practical environmental management to be obtained, as it precisely defined the optimum salt application and the required amount of replacement water, together with the cladode width for each plant growth stage using the accumulated thermal sum.
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Murillo-Posada, Juan Carlos, Silvia Salas, and Iván Velázquez-Abunader. "Factors affecting relative abundance of low-mobility fishing resources: spiny lobster in the Galapagos Marine Reserve." PeerJ 7 (July 8, 2019): e7278. http://dx.doi.org/10.7717/peerj.7278.
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Management of low-mobility or benthic fisheries is a difficult task because variation in the spatial distribution and population dynamics of the resources make the monitoring and assessment of these fisheries challenging. We assumed that environmental, spatial, and temporal factors can contribute to the variability of the relative abundance of such species; we used Generalized Additive Models for Location Scale and Shape (GAMLSS) to test this hypothesis using as a case study the lobster fishery (targeting two species) in the Galapagos Marine Reserve, Ecuador. We gathered data on each of the two species of lobster on a monthly basis over seven years, including: (a) onboard observers’ records of catch data, fishing effort, and ground location by trip, and (b) data from interviews undertaken with fishers at their arrival to port, recording the same type of information as obtained from onboard observers. We use this information to analyze the effect of the measured variables and to standardize the Catch per Unit Effort (CPUE) in each case, using the GAMLSS. For both species, the temperature, region, fishing schedule, month, distance, and the monitoring system were significant variables of the selected models associated with the variability of the catch rate. ForPanulirus penicillatus, CPUE was higher at night than during the day, and forPanulirus gracilisit was higher during the day. Increased temperature resulted in a decrease of CPUE values. It was evident that temporal, spatial scales and monitoring system can influence the variability of this indicator. We contend that the identification of drivers of change of relative abundance in low-mobility species can help to support the development of monitoring and assessment programs for this type of fisheries.
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Yu, Jisoo, Tae-Woong Kim, and Dong-Hyeok Park. "Future Hydrological Drought Risk Assessment Based on Nonstationary Joint Drought Management Index." Water 11, no. 3 (March 14, 2019): 532. http://dx.doi.org/10.3390/w11030532.
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As the environment changes, the stationarity assumption in hydrological analysis has become questionable. If nonstationarity of an observed time series is not fully considered when handling climate change scenarios, the outcomes of statistical analyses would be invalid in practice. This study established bivariate time-varying copula models for risk analysis based on the generalized additive models in location, scale, and shape (GAMLSS) theory to develop the nonstationary joint drought management index (JDMI). Two kinds of daily streamflow data from the Soyang River basin were used; one is that observed during 1976–2005, and the other is that simulated for the period 2011–2099 from 26 climate change scenarios. The JDMI quantified the multi-index of reliability and vulnerability of hydrological drought, both of which cause damage to the hydrosystem. Hydrological drought was defined as the low-flow events that occur when streamflow is equal to or less than Q80 calculated from observed data, allowing future drought risk to be assessed and compared with the past. Then, reliability and vulnerability were estimated based on the duration and magnitude of the events, respectively. As a result, the JDMI provided the expected duration and magnitude quantities of drought or water deficit.
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Gao, Lu, Jie Huang, Xingwei Chen, Ying Chen, and Meibing Liu. "Risk of Extreme Precipitation under Nonstationarity Conditions during the Second Flood Season in the Southeastern Coastal Region of China." Journal of Hydrometeorology 18, no. 3 (February 15, 2017): 669–81. http://dx.doi.org/10.1175/jhm-d-16-0119.1.
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Abstract This study analyzes the variation and risk changes of extreme precipitation under nonstationarity conditions using the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) and the Mann–Kendall (MK) test. The extreme precipitation series is extracted from the observations during the second flood season (July–September) from 1960 to 2012 derived from 86 meteorological stations in the southeastern coastal region of China. The trend of mean (Mn) and variance (Var) of extreme precipitation is detected by MK. Ten large-scale circulation variables and four greenhouse gases are selected to construct a climate change index and a human activity index, which are based on principal component analysis. The recurrence risk of extreme precipitation is calculated by GAMLSS while considering climate changes and human activities. The results demonstrate that the nonstationarity characteristic of extreme precipitation is widespread in this region. A significant increasing trend of Mn is found in Shanghai, eastern Zhejiang, and northern and southern Fujian. An enhanced Var is found in eastern Guangdong. A significant positive correlation exists between climate changes/human activities and Mn/Var, especially in Zhejiang and Fujian. Generally, the contribution of climate changes and human activities to Mn is greater than it is to Var. In this region, the precipitation amount of high-frequency (2-yr return period) and low-frequency (100-yr return period) events increases from inland to coastal and from north to south. The government should pay careful attention to these trends because the intensity of extreme precipitation events and their secondary disasters could result in serious losses.
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López, J., and F. Francés. "Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates." Hydrology and Earth System Sciences 17, no. 8 (August 12, 2013): 3189–203. http://dx.doi.org/10.5194/hess-17-3189-2013.
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Abstract. Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.
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López, J., and F. Francés. "Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates." Hydrology and Earth System Sciences Discussions 10, no. 3 (March 12, 2013): 3103–42. http://dx.doi.org/10.5194/hessd-10-3103-2013.
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Abstract. Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modeled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the distributions are modeled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies and to be used as predictive tools. Application of non-stationary analysis shows that the differences between the quantiles obtained and their stationary equivalents may be important over long periods of time.
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Wada, Yosuke, Norihiko Goto, Yoshiaki Kitaguchi, Masanori Yasuo, and Masayuki Hanaoka. "Referential equations for pulmonary diffusing capacity using GAMLSS models derived from Japanese individuals with near-normal lung function." PLOS ONE 17, no. 7 (July 21, 2022): e0271129. http://dx.doi.org/10.1371/journal.pone.0271129.
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Objective To generate appropriate reference values for the single-breath diffusing capacity of the lungs for carbon monoxide (DLCO), alveolar volume (VA), and the transfer coefficient of the lungs for carbon monoxide (KCO, often denoted as DLCO/VA) in the Japanese population. We also intended to assess the applicability of these values for the Japanese population by comparing them to those published by the Global Lung Function Initiative in 2017 (GLI-2017) and previous values. Methods In this retrospective study, we measured the spirometric indices, DLCO, VA, and KCO of the Japanese population aged 16–85 years. The lambda, mu, and sigma (LMS) method and the generalized additive models for the location, scale, and shape program in R were used to generate the reference values. Results We conducted a total of 390 tests. The GLI-2017 z-scores of DLCO were approximately zero, whereas those of KCO and VA were far from zero. In the present study, the mean square errors of the DLCO, VA, and KCO reference values were lower than the reference values derived from GLI-2017 and previous linear regression equations. Conclusions Reference values obtained in this study were more appropriate for our sample than those reported in GLI-2017. Differences between the two equations were attributed to underestimating KCO (DLCO / VA) and overestimating VA, respectively, by the GLI-2017 for the Japanese population.
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Pulcherio, R. S. L., M. N. A. Rocha, R. V. P. de Barros, E. S. Brito, D. P. Santos, A. J. Mendonça, C. Strüssmann, and R. H. S. Ferraz. "The influence of season, environment, sex, and body mass on biochemical profile of the freshwater turtle Phrynops geoffroanus (Schweigger, 1812)." Arquivo Brasileiro de Medicina Veterinária e Zootecnia 74, no. 5 (October 2022): 841–52. http://dx.doi.org/10.1590/1678-4162-12726.
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ABSTRACT We analyzed the influence of the season, the environment, and the sex, as well as the relation of body mass (BM) in the serum albumin (ALB), aspartate aminotransferase (AST), creatinine (C), creatine kinase (CK), phosphorus (P), total calcium (tCa), total protein (TP), urea (U), uric acid (UA), calcium:phosphorus ratio (Ca:P), and the globulin value (GV) of thirty individuals of Phrynops geoffroanus of the urban area of Cuiabá, Mato Grosso, Brazil. The modeling of biochemical parameters was performed using the Generalized Additive Models for Location, Scale and Shape (GAMLSS) to verify the influence of variables considered in this study on each of the biochemical parameters analyzed. The season influenced AST, CK, C, tCa, Ca:P and UA. The environment influenced tCa, Ca:P, U and UA. On the other hand, CK, tCa, P, Ca:P and U differed significantly between males and females. Regarding the BM, a relationship of this variable was observed with CK, C, tCa, P, U, UA and Ca:P. We concluded that the season, environment, sex, and body mass can influence the biochemical parameters of P. geoffroanus, and these factors should be routinely considered in the interpretation of laboratory results.
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Mateo-Abad, Maider, Kalliopi Vrotsou, María Padilla Ruiz, Alonso Montiel-Luque, María del Carmen Saucedo Figueredo, Mónica Machón, Francisco Rivas Ruiz, and Itziar Vergara. "Use of health care services according to functional performance in community-dwelling older adults in Spain. An approach using GAMLSS models." PLOS ONE 17, no. 11 (November 17, 2022): e0277681. http://dx.doi.org/10.1371/journal.pone.0277681.
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Functional performance in older adults is a predictor of survival and other health outcomes and its measurement is highly recommended in primary care settings. Functional performance and frailty are closely related concepts, and frailty status is associated with the use of health care services. However, there is insufficient evidence on the utilization of services profile according to the functional performance of older adults. The aim of this study was to assess the relationship between functional performance and the use of a wide range of health services in community-dwelling older adults. Generalized additive models for location, scale and shape were used to study these complex data of services utilization, from primary to hospital care. A total of 749 participants from two Spanish regions were followed up for 2 years. Of those, 276 (37%) presented low functional performance and 473 (63%) normal performance according to the Timed Up and Go test. The results showed that even after adjusting for burden of comorbidity and polypharmacy, participants with low functional performance used primary and secondary care health services more intensively, visited emergency rooms more often, and were hospitalized more frequently and for longer periods of time. A negative binomial distribution and a variant thereof were found to be the best models to describe health service utilization data. In conclusion, functionality should be considered as an important health indicator for tailoring the provision of health services for older adults.
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Shiau, Jenq-Tzong, and Yi-Ting Liu. "Nonstationary Analyses of the Maximum and Minimum Streamflow in Tamsui River Basin, Taiwan." Water 13, no. 6 (March 11, 2021): 762. http://dx.doi.org/10.3390/w13060762.
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This study aims to detect non-stationarity of the maximum and minimum streamflow regime in Tamsui River basin, northern Taiwan. Seven streamflow gauge stations, with at least 27-year daily records, are used to characterize annual maximum 1- and 2-day flows and annual minimum 1-, 7-, and 30-day flows. The generalized additive models for location, scale, and shape (GAMLSS) are used to dynamically detect evolution of probability distributions of the maximum and minimum flow indices with time. Results of time-covariate models indicate that stationarity is only noted in the 4 maximum flow indices out of 35 indices. This phenomenon indicates that the minimum flow indices are vulnerable to changing environments. A 16-category distributional-change scheme is employed to classify distributional changes of flow indices. A probabilistic distribution with complex variations of mean and variance is prevalent in the Tamsui River basin since approximate one third of flow indices (34.3%) belong to this category. To evaluate impacts of dams on streamflow regime, a dimensionless index called the reservoir index (RI) serves as an alternative covariate to model nonstationary probability distribution. Results of RI-covariate models indicate that 7 out of 15 flow indices are independent of RI and 80% of the best-fitted RI-covariate models are generally worse than the time-covariate models. This fact reveals that the dam is not the only factor in altering the streamflow regime in the Tamsui River, which is a significant alteration, especially the minimum flow indices. The obtained distributional changes of flow indices clearly indicate changes in probability distributions with time. Non-stationarity in the Tamsui River is induced by climate change and complex anthropogenic interferences.
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Scala, Pietro, Giuseppe Cipolla, Dario Treppiedi, and Leonardo Valerio Noto. "The Use of GAMLSS Framework for a Non-Stationary Frequency Analysis of Annual Runoff Data over a Mediterranean Area." Water 14, no. 18 (September 13, 2022): 2848. http://dx.doi.org/10.3390/w14182848.
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Climate change affects all the components of the hydrological cycle. Starting from precipitation distribution, climate alterations have direct effects on both surface water and groundwater in terms of their quantity and quality. These effects lead to modifications in water availability for agriculture, ecology and other social uses. Change in rainfall patterns also affects the runoff of natural rivers. For this reason, studying runoff data according to classical hydrological approaches, i.e., statistical inference methods that exploit stationary probability distributions, might result in missing important information relevant to climate change. From this point of view, a new approach has to be found in the study of this type of data that allows for non-stationary analysis. In this study, the statistical framework known as Generalized Additive Models for Location, Scale and Shape (GAMLSS), which can be used to carry out non-stationary statistical analyses, was applied in a non-stationary frequency analysis of runoff data collected by four gauges widely distributed across Sicily (Italy) in the period 1916–1998. A classical stationary frequency analysis of these runoff data was followed by a different non-stationary frequency analysis; while the first was made using annual rainfall as a covariate, with the aim of understanding how certain statistical parameters of runoff distribution vary with changes in rainfall, the second derived information about the temporal variability of runoff frequencies by considering time as a covariate. A comparison between stationary and non-stationary approaches was carried out using the Akaike information criterion as a performance metric. After analyzing four different probability distributions, the non-stationary model with annual rainfall as a covariate was found to be the best among all those examined, and the three-parameter lognormal the most frequently preferred distribution.
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Wen, Qingzhi, Peng Sun, Qiang Zhang, and Hu Li. "Nonstationary Ecological Instream Flow and Relevant Causes in the Huai River Basin, China." Water 13, no. 4 (February 13, 2021): 484. http://dx.doi.org/10.3390/w13040484.
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Based on the daily precipitation data during 1960–2016 at 72 stations and the daily streamflow data during 1956–2016 at 7 hydrological stations in the Huai River Basin (HRB), China, eco-surplus and eco-deficit under influences of abrupt streamflow behaviors were analyzed using Flow Duration Curve (FDC). The relations between indicators of hydrological alteration (IHA) and ecological indicators (Shannon Index, SI) were quantified, investigating impacts of altered hydrological processes on the evaluations of the ecological instream flow. Besides, we also quantified fractional contributions of climatic indices to nonstationary ecological instream flow using the Generalized Additive Models for Location Scale and Shape (GAMLSS) framework. While the possible impact of human activities on ecological instream flow will be revealed based on land use changes data. The results indicated that: (1) FDC is subject to general decrease due to hydrological alterations, and most streamflow components are lower than 25% FDC. We found increased eco-deficit and decreased eco-surplus due to altered hydrological processes. The FDC of the streamflow in the main stream of the HRB is lower than that along the tributaries of the HRB. Eco-surplus (eco-deficit) changes are in good line with precipitation anomaly changes during the Spring, Autumn and Winter periods. However, the hydrological alterations due to hydrological regulations by the reservoirs are the primary cause behind the mismatch between ecological instream flow and precipitation anomalies during summer; (2) Annual and seasonal eco-surplus (eco-deficit) is decreasing (increasing) and that during winter season is an exception. Although higher eco-surplus in winter than in other seasons, the eco-surplus is decreasing persistently and the 21st century witnessed the lowest eco-surplus along the main stream of the HRB. Meanwhile, the Shannon index indicated decreased ecological diversity across the HRB; (3) The ecological instream flow is highly sensitive to The Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Niño 3.4 Sea Surface Temperature Index (Nino3.4). Meanwhile, the ecological instream flow along the mainstream of the HRB is highly sensitive to climate indices. While the ecological instream flow by GAMLSS model has better fitting performance in describing the extreme values and local trends.
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Fernández, Itziar, Amalia Enríquez-de-Salamanca, Alejandro Portero, Carmen García-Vázquez, Margarita Calonge, and José M. Herreras. "Age- and Sex-Adjusted Reference Intervals in Tear Cytokine Levels in Healthy Subjects." Applied Sciences 11, no. 19 (September 26, 2021): 8958. http://dx.doi.org/10.3390/app11198958.
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Alterations in tear cytokine levels have been associated with various ocular disorders as compared to those in healthy subjects. However, age and sex are not always considered in these comparisons. In this study we aimed to establish age and sex reference intervals (RIs) for tear cytokine levels in healthy people. Tear samples were taken from 75 males and 82 females, aged 18–88 years, and tear cytokine levels were determined. Age- and sex-adjusted RIs for epidermal growth factor (EGF), fractalkine, interleukin (IL)-1 receptor antagonist (RA), IL-7, IL-8, interferon inducible protein (IP)-10, monocyte chemotactic protein (MCP)-1, and vascular endothelial growth factor (VEGF) tear cytokine levels in a healthy sample were established using generalized additive for location, scale and shape (GAMLSS) models. RIs were tested in two external samples: a validation sample of 40 individuals with normal results at four Dry Eye Disease (DED) clinical diagnostic tests (OSDI, T-BUT, corneal staining and Schirmer test); and a utility sample of 13 severe DED cases. IL-1RA, IL-8, IP-10, and MCP-1 levels showed a positive association with age, while EGF was negatively correlated. IL-7 concentration increased up to 40 years and again after 70 years, observing a quasi-linear decrease between them. For VEGF, higher levels were observed in the middle-aged range. Regarding sex-influence, fractalkine tear levels were higher in men, whereas those of IL-7, IL-8, and IP-10 were higher in women. Using the estimated age- and sex-adjusted RIs, more than 92% of the validation sample was correctly classified, and 100% of the severe DED patients in the utility sample had concentrations outside the RIs in at least two of the cytokines evaluated.
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Ramires, Thiago G., Gauss M. Cordeiro, Michael W. Kattan, Niel Hens, and Edwin MM Ortega. "Predicting the cure rate of breast cancer using a new regression model with four regression structures." Statistical Methods in Medical Research 27, no. 11 (February 23, 2017): 3207–23. http://dx.doi.org/10.1177/0962280217695344.
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Cure fraction models are useful to model lifetime data with long-term survivors. We propose a flexible four-parameter cure rate survival model called the log-sinh Cauchy promotion time model for predicting breast carcinoma survival in women who underwent mastectomy. The model can estimate simultaneously the effects of the explanatory variables on the timing acceleration/deceleration of a given event, the surviving fraction, the heterogeneity, and the possible existence of bimodality in the data. In order to examine the performance of the proposed model, simulations are presented to verify the robust aspects of this flexible class against outlying and influential observations. Furthermore, we determine some diagnostic measures and the one-step approximations of the estimates in the case-deletion model. The new model was implemented in the generalized additive model for location, scale and shape package of the R software, which is presented throughout the paper by way of a brief tutorial on its use. The potential of the new regression model to accurately predict breast carcinoma mortality is illustrated using a real data set.
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Machado, M. J., B. A. Botero, J. López, F. Francés, A. Díez-Herrero, and G. Benito. "Flood frequency analysis of historical flood data under stationary and non-stationary modelling." Hydrology and Earth System Sciences 19, no. 6 (June 2, 2015): 2561–76. http://dx.doi.org/10.5194/hess-19-2561-2015.
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Abstract. Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged records) improved the estimates of the probabilities of rare floods (return intervals of 100 yr and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 yr) has changed over the last 500 yr due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful in providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.
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Machado, M. J., B. A. Botero, J. López, F. Francés, A. Díez-Herrero, and G. Benito. "Flood frequency analysis of historical flood data under stationary and non-stationary modelling." Hydrology and Earth System Sciences Discussions 12, no. 1 (January 14, 2015): 525–68. http://dx.doi.org/10.5194/hessd-12-525-2015.
Full textAbstract:
Abstract. Historical records are an important source of information about extreme and rare floods with a great value to establish a reliable flood return frequency. The use of long historic records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 year flood record from the Tagus River in Aranjuez (Central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their implications on hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations on flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation index (NAO index). Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators; (b) a time–varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, that incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged record) improved the estimates of the probabilities of rare floods (return intervals of 100 year and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 year) has changed over the last 500 year due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful on providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.
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Guimarães, Paulo Ricardo Bittencourt, Ricardo Berger, Fernando Lucambio Perez, and Paulo de Tarso Lara Pires. "RELAÇÕES ENTRE AS DOENÇAS RESPIRATÓRIAS E A POLUIÇÃO ATMOSFÉRICA E VARIÁVEIS CLIMÁTICAS NA CIDADE DE CURITIBA, PARANÁ, BRASIL." FLORESTA 42, no. 4 (December 31, 2012): 817. http://dx.doi.org/10.5380/rf.v42i4.24628.
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ResumoNeste estudo, foram observados níveis de concentrações de poluentes atmosféricos da cidade de Curitiba, no período de novembro de 2003 a junho de 2008, da estação automática de monitoramento da praça Ouvidor Pardinho. O objetivo foi desenvolver uma metodologia de modelagem estatística que explique o número de notificações de doenças respiratórias registradas em idosos (acima de 60 anos) e crianças (abaixo de 5 anos). Além das concentrações de poluentes, algumas variáveis climáticas foram analisadas. Após estudo de diversas metodologias estatísticas, considerou-se mais adequado o ajuste de Modelos Aditivos Generalizados para Locação, Escala e Forma. Os modelos ajustados apresentaram resultados satisfatórios e consideraram como variáveis significativas as partículas inaláveis e a temperatura. Além disso, verificou-se que existe redução proporcional do número de notificações de doenças respiratórias no período observado, em consequência da redução dos níveis de concentração de partículas inaláveis no município de Curitiba. Os resultados encontrados podem ter sido influenciados pelas campanhas de vacinação de idosos, pela utilização de motores menos poluentes no transporte coletivo, pelo aumento da produção de carros “flex” e também pela grande cobertura vegetal existente no município, responsável pelos mais altos índices de área verde por habitante entre os grandes centros urbanos do Brasil. AbstractRelation between respiratory diseases and air pollution and climatic variables, in Curitiba, Parana, Brazil. In this research, concentration levels of atmospheric pollutants were observed between November 2003 and June 2008 from an automated monitoring station located at Ouvidor Pardinho Square, City of Curitiba. It aimed to develop a methodology of statistical model in order to explain the number of notifications of respiratory diseases registered in the elderly (above the age of 60 years) and children (below the age of 5 years). Apart from the concentration of pollutants, climatic variables were also analyzed. After study of several statistical methodologies, it was considered that the most adequate was an adjustment of the Generalized Additive Models for Location, Scale and Shape. The adjusted models presented satisfactory results and considered as significant variables the particulate matter and temperature. It was also observed a proportional reduction in the number of notifications of respiratory diseases within the observed period as a consequence of the concentration level reduction of the particulate matter in the city. These results may have been influenced by vaccination campaigns involving the elderly, by use of less polluting engines in the public transportation system, by an increase in production of “flex”- type cars and also by the large vegetation coverage in the city, which is responsible for one of the highest indexes of green area per inhabitant amongst the large urban centers in Brazil.Keywords: Generalized linear models; pollutants; particulate matter; GAMLSS.
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Liew, Bernard X. W., David Rugamer, Kim Duffy, Matthew Taylor, and Jo Jackson. "The mechanical energetics of walking across the adult lifespan." PLOS ONE 16, no. 11 (November 12, 2021): e0259817. http://dx.doi.org/10.1371/journal.pone.0259817.
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Purpose Understanding what constitutes normal walking mechanics across the adult lifespan is crucial to the identification and intervention of early decline in walking function. Existing research has assumed a simple linear alteration in peak joint powers between young and older adults. The aim of the present study was to quantify the potential (non)linear relationship between age and the joint power waveforms of the lower limb during walking. Methods This was a pooled secondary analysis of the authors’ (MT, KD, JJ) and three publicly available datasets, resulting in a dataset of 278 adults between the ages of 19 to 86 years old. Three-dimensional motion capture with synchronised force plate assessment was performed during self-paced walking. Inverse dynamics were used to quantity joint power of the ankle, knee, and hip, which were time-normalized to 100 stride cycle points. Generalized Additive Models for location, scale and shape (GAMLSS) was used to model the effect of cycle points, age, walking speed, stride length, height, and their interaction on the outcome of each joint’s power. Results At both 1m/s and 1.5 m/s, A2 peaked at the age of 60 years old with a value of 3.09 (95% confidence interval [CI] 2.95 to 3.23) W/kg and 3.05 (95%CI 2.94 to 3.16), respectively. For H1, joint power peaked with a value of 0.40 (95%CI 0.31 to 0.49) W/kg at 1m/s, and with a value of 0.78 (95%CI 0.72 to 0.84) W/kg at 1.5m/s, at the age of 20 years old. For H3, joint power peaked with a value of 0.69 (95%CI 0.62 to 0.76) W/kg at 1m/s, and with a value of 1.38 (95%CI 1.32 to 1.44) W/kg at 1.5m/s, at the age of 70 years old. Conclusions Findings from this study do not support a simple linear relationship between joint power and ageing. A more in-depth understanding of walking mechanics across the lifespan may provide more opportunities to develop early clinical diagnostic and therapeutic strategies for impaired walking function. We anticipate that the present methodology of pooling data across multiple studies, is a novel and useful research method to understand motor development across the lifespan.