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Nogués-Bravo, D. "Comparing regression methods to predict species richness patterns." Web Ecology 9, no. 1 (December 9, 2009): 58–67. http://dx.doi.org/10.5194/we-9-58-2009.
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Abstract. Multivariable regression models have been used extensively as spatial modelling tools. However, other regression approaches are emerging as more efficient techniques. This paper attempts to present a synthesis of Generalised Regression Models (Generalized Linear Models, GLMs, Generalized Additive Models, GAMs), and a Geographically Weighted Regression, GWR, implemented in a GAM, explaining their statistical formulations and assessing improvements in predictive accuracy compared with linear regressions. The problems associated with these approaches are also discussed. A digital database developed with Geographic Information Systems (GIS), including environmental maps and bird species richness distribution in northern Spain, is used for comparison of the techniques. GWR using splines has shown the highest improvement in accounted deviance when compared with traditional linear regression approach, followed by GAM and GLM.
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Vencálek, Ondřej, Karel Hron, and Peter Filzmoser. "A comparison of generalised linear models and compositional models for ordered categorical data." Statistical Modelling 20, no. 3 (January 15, 2019): 249–73. http://dx.doi.org/10.1177/1471082x18816540.
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Ordered categorical data occur in many applied fields, such as geochemistry, econometrics, sociology and demography or even transportation research, for example, in the form of results from various questionnaires. There are different possibilities for modelling proportions of individual categories. Generalised linear models (GLMs) are traditionally used for this purpose, but also methods of compositional data analysis (CoDa) can be considered. Here, both approaches are compared in depth. Particularly, different assumptions of the models on variability are highlighted. Advantages and disadvantages of individual models are pointed out. While the CoDa model may be inappropriate when the variability of the compositional coordinates depends on the regressors, for example, due to different total counts on which the coordinates are based, the GLM may underestimate the uncertainty of the predictions considerably in case of large-scale data.
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Saavedra, Angeles, Javier Taboada, María Araújo, and Eduardo Giráldez. "Generalized Linear Spatial Models to Predict Slate Exploitability." Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/531062.
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The aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatial model (GLSMs) was fitted in order to explore relationship between exploitability and different explanatory variables that characterize slate quality. Modelling the influence of these variables and analysing the spatial distribution of the model residuals yielded a GLSM that allows slate exploitability to be predicted more effectively than when using generalized linear models (GLM), which do not take spatial dependence into account. Studying the residuals and comparing the prediction capacities of the two models lead us to conclude that the GLSM is more appropriate when the response variable presents spatial distribution.
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Bar Massada, Avi, Alexandra D. Syphard, Susan I. Stewart, and Volker C. Radeloff. "Wildfire ignition-distribution modelling: a comparative study in the Huron–Manistee National Forest, Michigan, USA." International Journal of Wildland Fire 22, no. 2 (2013): 174. http://dx.doi.org/10.1071/wf11178.
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Wildfire ignition distribution models are powerful tools for predicting the probability of ignitions across broad areas, and identifying their drivers. Several approaches have been used for ignition-distribution modelling, yet the performance of different model types has not been compared. This is unfortunate, given that conceptually similar species-distribution models exhibit pronounced differences among model types. Therefore, our goal was to compare the predictive performance, variable importance and the spatial patterns of predicted ignition-probabilities of three ignition-distribution model types: one parametric, statistical model (Generalised Linear Models, GLM) and two machine-learning algorithms (Random Forests and Maximum Entropy, Maxent). We parameterised the models using 16 years of ignitions data and environmental data for the Huron–Manistee National Forest in Michigan, USA. Random Forests and Maxent had slightly better prediction accuracies than did GLM, but model fit was similar for all three. Variables related to human population and development were the best predictors of wildfire ignition locations in all models (although variable rankings differed slightly), along with elevation. However, despite similar model performance and variables, the map of ignition probabilities generated by Maxent was markedly different from those of the two other models. We thus suggest that when accurate predictions are desired, the outcomes of different model types should be compared, or alternatively combined, to produce ensemble predictions.
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Bekar, İsmail, and Çağatay Tavşanoğlu. "Modelling the drivers of natural fire activity: the bias created by cropland fires." International Journal of Wildland Fire 26, no. 10 (2017): 845. http://dx.doi.org/10.1071/wf16183.
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Wildland and cropland fires, which differ considerably in fire regime characteristics, have often been evaluated jointly to estimate regional or global fire regimes using satellite-based fire activity data. We hypothesised that excluding cropland fires will change the output of the models regarding the drivers of natural fire activity. We modelled MODIS fire activity data of western and southern Turkey for the years 2000–2015 using binomial generalised linear models in which many climatic, anthropogenic and geographic factors were included as predictor variables. For modelling, we used different datasets created by the exclusion of various cropland and vegetation land cover classes. More fire activity was observed as the number of cropland-dominated cells increased in a dataset. The explained deviance (%) of the binomial GLM differed substantially in the separate datasets for most of the variables. Moreover, excluding croplands gradually from the overall dataset resulted in a substantial decrease in the explained deviance (%) in the models for all variables. The results suggest that cropland fires have a significant effect on the output of fire regime models. Therefore, a clear distinction should be drawn between wildland and cropland fires in such models for a better understanding of natural fire activity.
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Osawa, Takeshi, Hiromune Mitsuhashi, Yuta Uematsu, and Atushi Ushimaru. "Bagging GLM: Improved generalized linear model for the analysis of zero-inflated data." Ecological Informatics 6, no. 5 (September 2011): 270–75. http://dx.doi.org/10.1016/j.ecoinf.2011.05.003.
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Lovegrove, Gordon R., and Tarek Sayed. "Macro-level collision prediction models for evaluating neighbourhood traffic safety." Canadian Journal of Civil Engineering 33, no. 5 (May 1, 2006): 609–21. http://dx.doi.org/10.1139/l06-013.
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This study describes the development of macro-level (i.e., neighbourhood or traffic zone level) collision prediction models using data from 577 neighbourhoods across the Greater Vancouver Regional District. The objective is to provide a safety planning decision-support tool that facilitates a proactive approach to community planning which addresses road safety before problems emerge. The models are developed using the generalized linear regression modelling (GLM) technique assuming a negative binomial error structure. The resulting models relate traffic collisions to neighbourhood characteristics such as traffic volume, demographics, network shape, and transportation demand management. Several models are presented for total or severe collisions in rural or urban zones using measured and (or) modelled data. It is hoped that quantifying a predictive traffic safety – neighbourhood planning relationship will facilitate improved decisions by community planners and engineers and, ultimately, facilitate improved neighbourhood traffic safety for residents and other road users.Key words: neighbourhood safety, macro-level collision prediction models, road safety, safety planning, transportation demand management, sociodemographic, generalized linear regression modelling.
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Karl, Florian M., Jennifer Smith, Shannon Piedt, Kate Turcotte, and Ian Pike. "Applying the health action process approach to bicycle helmet use and evaluating a social marketing campaign." Injury Prevention 24, no. 4 (August 5, 2017): 288–95. http://dx.doi.org/10.1136/injuryprev-2017-042399.
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BackgroundBicycle injuries are of concern in Canada. Since helmet use was mandated in 1996 in the province of British Columbia, Canada, use has increased and head injuries have decreased. Despite the law, many cyclists do not wear a helmet. Health action process approach (HAPA) model explains intention and behaviour with self-efficacy, risk perception, outcome expectancies and planning constructs. The present study examines the impact of a social marketing campaign on HAPA constructs in the context of bicycle helmet use.MethodA questionnaire was administered to identify factors determining helmet use. Intention to obey the law, and perceived risk of being caught if not obeying the law were included as additional constructs. Path analysis was used to extract the strongest influences on intention and behaviour. The social marketing campaign was evaluated through t-test comparisons after propensity score matching and generalised linear modelling (GLM) were applied to adjust for the same covariates.Results400 cyclists aged 25–54 years completed the questionnaire. Self-efficacy and Intention were most predictive of intention to wear a helmet, which, moderated by planning, strongly predicted behaviour. Perceived risk and outcome expectancies had no significant impact on intention. GLM showed that exposure to the campaign was significantly associated with higher values in self-efficacy, intention and bicycle helmet use.ConclusionSelf-efficacy and planning are important points of action for promoting helmet use. Social marketing campaigns that remind people of appropriate preventive action have an impact on behaviour.
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Chun, K. P., H. S. Wheater, and C. J. Onof. "Streamflow estimation for six UK catchments under future climate scenarios." Hydrology Research 40, no. 2-3 (April 1, 2009): 96–112. http://dx.doi.org/10.2166/nh.2009.086.
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Possible changes in streamflow in response to climate variation are crucial for anthropological and ecological systems. However, estimates of precipitation under future climate scenarios are notoriously uncertain. In this article, rainfall time series are generated by the generalized linear model (GLM) approach in which stochastic time series are generated using alternative climate model output variables and potential evaporation series estimated by a temperature method. These have been input to a conceptual rainfall–runoff model (pd4-2par) to simulate the daily streamflows for six UK catchments for a set of climate scenarios using seven global circulation models (GCMs) and regional circulation models (RCMs). The performance of the combined methodology in reproducing observed streamflows is generally good. Results of future climate scenarios show significant variability between different catchments, and very large variability between different climate models. It is concluded that the GLM methodology is promising, and can readily be extended to support distributed hydrological modelling.
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Iyit, Neslihan. "Modelling world energy security data from multinomial distribution by generalized linear model under different cumulative link functions." Open Chemistry 16, no. 1 (April 30, 2018): 377–85. http://dx.doi.org/10.1515/chem-2018-0053.
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AbstractEnergy securityis one of the major components of energy sustainability in the world’s energy performance. In this study,energy securityis taken as an ordinal response variable coming from the multinomial distribution with the energy grade levelsA,B,C, andD. Thereafter, the worldenergy securitydata is tried to be statistically modelled by usinggeneralized linear model (GLM)approach for the ordinal response variable under different cumulative link functions. The cumulative link functions comparatively used in this study are cumulative logit, cumulative probit, cumulative complementary log-log, cumulative Cauchit, and cumulative negative log-log. In order to avoid a multicollinearity problem in the data structure, principal component analysis (PCA) technique is integrated with theGLMapproach for the ordinal response variable. In this study, statistically, the importance of determining the best cumulative link function on the accuracy of parameter estimates, confidence intervals, and hypothesis tests in theGLMfor the multinomially distributed response variable is highlighted. In terms of energy evaluation, by usingcumulative logitas the best cumulative link function,energy sources consumptions,electricity productions from nuclear energy,natural gas,oil,coal,and hydroelectric,energy use per capita and energy importsare found to have statistically significant effects onenergy securityin the world’s energy performance.
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Capinha, César, Franz Essl, Hanno Seebens, Henrique Miguel Pereira, and Ingolf Kühn. "Models of alien species richness show moderate predictive accuracy and poor transferability." NeoBiota 38 (June 6, 2018): 77–96. http://dx.doi.org/10.3897/neobiota.38.23518.
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Robust predictions of alien species richness are useful to assess global biodiversity change. Nevertheless, the capacity to predict spatial patterns of alien species richness remains largely unassessed. Using 22 data sets of alien species richness from diverse taxonomic groups and covering various parts of the world, we evaluated whether different statistical models were able to provide useful predictions of absolute and relative alien species richness, as a function of explanatory variables representing geographical, environmental and socio-economic factors. Five state-of-the-art count data modelling techniques were used and compared: Poisson and negative binomial generalised linear models (GLMs), multivariate adaptive regression splines (MARS), random forests (RF) and boosted regression trees (BRT). We found that predictions of absolute alien species richness had a low to moderate accuracy in the region where the models were developed and a consistently poor accuracy in new regions. Predictions of relative richness performed in a superior manner in both geographical settings, but still were not good. Flexible tree ensembles-type techniques (RF and BRT) were shown to be significantly better in modelling alien species richness than parametric linear models (such as GLM), despite the latter being more commonly applied for this purpose. Importantly, the poor spatial transferability of models also warrants caution in assuming the generality of the relationships they identify, e.g. by applying projections under future scenario conditions. Ultimately, our results strongly suggest that predictability of spatial variation in richness of alien species richness is limited. The somewhat more robust ability to rank regions according to the number of aliens they have (i.e. relative richness), suggests that models of aliens species richness may be useful for prioritising and comparing regions, but not for predicting exact species numbers.
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ter Braak, Cajo J. F., Pedro Peres-Neto, and Stéphane Dray. "A critical issue in model-based inference for studying trait-based community assembly and a solution." PeerJ 5 (January 12, 2017): e2885. http://dx.doi.org/10.7717/peerj.2885.
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Statistical testing of trait-environment association from data is a challenge as there is no common unit of observation: the trait is observed on species, the environment on sites and the mediating abundance on species-site combinations. A number of correlation-based methods, such as the community weighted trait means method (CWM), the fourth-corner correlation method and the multivariate method RLQ, have been proposed to estimate such trait-environment associations. In these methods, valid statistical testing proceeds by performing two separate resampling tests, one site-based and the other species-based and by assessing significance by the largest of the twop-values (thepmaxtest). Recently, regression-based methods using generalized linear models (GLM) have been proposed as a promising alternative with statistical inference via site-based resampling. We investigated the performance of this new approach along with approaches that mimicked thepmaxtest using GLM instead of fourth-corner. By simulation using models with additional random variation in the species response to the environment, the site-based resampling tests using GLM are shown to have severely inflated type I error, of up to 90%, when the nominal level is set as 5%. In addition, predictive modelling of such data using site-based cross-validation very often identified trait-environment interactions that had no predictive value. The problem that we identify is not an “omitted variable bias” problem as it occurs even when the additional random variation is independent of the observed trait and environment data. Instead, it is a problem of ignoring a random effect. In the same simulations, the GLM-basedpmaxtest controlled the type I error in all models proposed so far in this context, but still gave slightly inflated error in more complex models that included both missing (but important) traits and missing (but important) environmental variables. For screening the importance of single trait-environment combinations, the fourth-corner test is shown to give almost the same results as the GLM-based tests in far less computing time.
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Hay, Fiona R., Andrew Mead, and Mark Bloomberg. "Modelling seed germination in response to continuous variables: use and limitations of probit analysis and alternative approaches." Seed Science Research 24, no. 3 (July 7, 2014): 165–86. http://dx.doi.org/10.1017/s096025851400021x.
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AbstractProbit-based models relating a proportional response variable to a temporal explanatory variable, assuming that the times to response are normally distributed within the population, have been used in seed biology for describing the rate of loss of viability during seed ageing and the progress of germination over time in response to environmental signals (e.g. water, temperature). These models may be expressed as generalized linear models (GLMs) with a probit (cumulative normal distribution) link function, and, using GLM fitting procedures in current statistical software, parameters of these models are efficiently estimated while taking into account the binomial error distribution of the dependent variable. The fitted parameters can then be used to calculate the ‘traditional’ model parameters, such as the hydro- or hydrothermal time constant, the mean or median response of the seeds (e.g. mean time to death, median base water potential), and the standard deviation of the normal distribution of that response. Furthermore, through consideration of the deviance and residuals, performing model evaluation and modification can lead to improved understanding of the underlying physiological/ecological processes. However, fitting a binomial GLM is not appropriate for the cumulative count data often collected from germination studies, as successive observations are not independent, and time-to-event/survival analysis should be considered instead. This review discusses well-known probit-based models, providing advice on how to collect appropriate data and fit the models to those data, and gives an overview of alternative analysis approaches to improve understanding of the underlying mechanisms of seed dormancy and germination behaviour.
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Shen, Bo-Wen. "Aggregated Negative Feedback in a Generalized Lorenz Model." International Journal of Bifurcation and Chaos 29, no. 03 (March 2019): 1950037. http://dx.doi.org/10.1142/s0218127419500378.
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In this study, we first present a generalized Lorenz model (LM) with [Formula: see text] modes, where [Formula: see text] is an odd number that is greater than three. The generalized LM (GLM) is derived based on a successive extension of the nonlinear feedback loop (NFL) with additional high wavenumber modes. By performing a linear stability analysis with [Formula: see text] and [Formula: see text], we illustrate that: (1) within the 3D, 5D, and 7D LMs, the appearance of unstable nontrivial critical points requires a larger Rayleigh parameter in a higher-dimensional LM and (2) within the 9DLM, nontrivial critical points are stable. By comparing the GLM with various numbers of modes, we discuss the aggregated negative feedback enabled by the extended NFL and its role in stabilizing solutions in high-dimensional LMs. Our analysis indicates that the 9DLM is the lowest order generalized LM with stable nontrivial critical points for all Rayleigh parameters greater than one. As shown by calculations of the ensemble Lyapunov exponent, the 9DLM still produces chaotic solutions. Within the 9DLM, a larger critical value for the Rayleigh parameter, [Formula: see text], is required for the onset of chaos as compared to a [Formula: see text] for the 3DLM, a [Formula: see text] for the 5DLM, and a [Formula: see text] for the 7DLM. In association with stable nontrivial critical points that may lead to steady-state solutions, the appearance of chaotic orbits indicates the important role of a saddle point at the origin in producing the sensitive dependence of solutions on initial conditions. The 9DLM displays the coexistence of chaotic and steady-state solutions at moderate Rayleigh parameters and the coexistence of limit cycle and steady-state solutions at large Rayleigh parameters. The first kind of coexistence appears within a smaller range of Rayleigh parameters in lower-dimensional LMs (i.e. [Formula: see text] within the 3DLM) but in a wider range of Rayleigh parameters within the 9DLM (i.e. [Formula: see text]). The second kind of coexistence has never been reported in high-dimensional Lorenz systems.
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Austin, MP. "Modelling the Environmental Niche of Plants: Implications for Plant Community Response to Elevated CO2 Levels." Australian Journal of Botany 40, no. 5 (1992): 615. http://dx.doi.org/10.1071/bt9920615.
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No simple natural gradients in CO2 concentration exist for testing predictions about changes in plant communities in response to elevated CO2. However indirect effects of CO2 via temperature increases can be tested by reference to natural analogues. Physiologists, vegetation modellers of climate change and community ecologists assume very different temperature responses for plants. Physiologists often assume a skewed non-monotonic curve with a tail towards low temperatures, forest modellers using FORET type models, a symmetric curve, and community ecologists a skewed response with a tail towards high temperatures. These assumptions are reviewed in relation to niche theory, and recent propositions concerning the continuum concept. Confusion exists between the different approaches over the shape of response curves to temperature. Distinctions need to be made between responses due to growth (physiological response), potential fitness (fundamental niche) and observed performance (realized niche). These types of response should be quantified and related to each other if process-models are to be tested for predictive success by reference to naturally occurring communities and temperature gradients. An example of a statistical method for quantifying the realized environmental niche response of a species to temperature is provided. It is based on generalised linear modelling (GLM) of presence/absence data on Eucalyptus fastigata for 8377 sites in southern New South Wales, Australia. Seven environmental variables or factors are considered: mean annual temperature, mean annual rainfall, mean monthly solar radiation, topographic position, rainfall seasonality, lithology, and soil nutrient status. The temperature response is modelled with a β-function, logy = a + α log ( t - a ) + δ log ( b - t), where t is temperature and letters are parameters. The probability of occurrence is shown to be a skewed function of mean annual temperature. Any process-models of climate change for vegetation incorporating temperature changes due to elevated CO2 must be capable of generating such realised environmental niche responses for species.
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Marzialetti, Flavio, Manuele Bazzichetto, Silvia Giulio, Alicia T. R. Acosta, Angela Stanisci, Marco Malavasi, and Maria Laura Carranza. "Modelling Acacia saligna invasion on the Adriatic coastal landscape: An integrative approach using LTER data." Nature Conservation 34 (May 3, 2019): 127–44. http://dx.doi.org/10.3897/natureconservation.34.29575.
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Invasive Alien Species (IAS) pose a major threat to biodiversity and ecosystem services worldwide. Even if preventing biological invasions should be the most cost-effective way to minimise the impact of IAS on biodiversity, new efforts are necessary to identify early signs of invasion and to assess invasion risk. In this context, the implementation of invasive Species Distribution Models (iSDMs) could represent a sound instrument that merits further research. Acaciasaligna is an Australian vascular plant introduced into Europe during the last half century and is one of the most aggressive IAS in the Mediterranean basin. In this work, we model the occurrence of A.saligna in the coastal landscapes of central Italy (Adriatic coast) while accounting for the simultaneous effect of multiple factors (propagule pressure, abiotic, biotic factors). The iSDM for A.saligna was implemented on a representative tract of the Adriatic coast in central Italy (Molise region), largely included in two Long-Term Ecological Research (LTER) sites which actively contribute to the description of the considered ecosystem status and possible future trends. By using a Generalised Linear Model (GLM) with a binomial distribution of errors based on field and cartographic geo-referenced data, we examined the statistical relationship between the occurrence of A.saligna and a comprehensive set of environmental factors. The iSDM effectively captured the role of the different variables in determining the occurrence of A.saligna in the coastal dunes. Its occurrence is primarily related to Wooded dunes with Pinuspinea and/or P.pinaster (EU Habitat 2270) and distance from the sea and, to a lesser extent, with distance from roads and rivers. This research provides a first exploratory analysis of the environmental characteristics that promote the rapid growth and development of A.saligna in Italian dune ecosystems, identifying the habitats that are mainly affected by the invasive process in coastal areas and, by doing so, contributing to filling the gap between theory and practice in conservation decision-making. Finally, the LTER network benefitted from this research, confirming its relevance in providing useful information for modelling and monitoring invasion processes.
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Harati, Saeed, Liliana Perez, and Roberto Molowny-Horas. "Integrating Neighborhood Effect and Supervised Machine Learning Techniques to Model and Simulate Forest Insect Outbreaks in British Columbia, Canada." Forests 11, no. 11 (November 18, 2020): 1215. http://dx.doi.org/10.3390/f11111215.
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Background and Objectives: Modelling and simulation of forest land cover change due to epidemic insect outbreaks are powerful tools that can be used in planning and preparing strategies for forest management. In this study, we propose an integrative approach to model land cover changes at a provincial level, using as a study case the simulation of the spatiotemporal dynamics of mountain pine beetle (MPB) infestation over the lodgepole pine forest of British Columbia (BC), Canada. This paper aims to simulate land cover change by applying supervised machine learning techniques to maps of MPB-driven deforestation. Materials and Methods: We used a 16-year series (1999–2014) of spatial information on annual mortality of pine trees due to MPB attacks, provided by the BC Ministry of Forests. We used elevation, aspect, slope, ruggedness, and weighted neighborhood of infestation as predictors. We implemented (a) generalized linear regression (GLM), and (b) random forest (RF) algorithms to simulate forestland cover changes due to MPB between 2005 and 2014. To optimize the ability of our models to predict MPB infestation in 2020, a cross-validation procedure was implemented. Results: Simulating infestations from 2008 to 2014, RF algorithms produced less error than GLM. Our simulations for the year 2020 confirmed the predictions from the BC Ministry of Forest by forecasting a slower rate of spread in future MPB infestations in the province. Conclusions: Integrating neighborhood effects as variables in model calibration allows spatiotemporal complexities to be simulated.
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Zhao, Tongwei, Guangyun Mao, and Ming Chen. "The Role of Change Rates of CYFRA21-1 and CEA in Predicting Chemotherapy Efficacy for Non-Small-Cell Lung Cancer." Computational and Mathematical Methods in Medicine 2021 (September 21, 2021): 1–7. http://dx.doi.org/10.1155/2021/1951364.
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Background. Cytokeratin 19 fragment 21-1 (CYFRA21-1) and carcinoembryonic antigen (CEA) are effective prognostic biomarkers for lung cancer. This study investigated the predictive effects of change rates of CYFRA21-1 and CEA before and after the first cycles of chemotherapy on advanced IIIb/IIIc or IV stage non-small-cell lung cancer (NSCLC) patients. Methods. Data of 103 NSCLC patients who received chemotherapy in Zhejiang Provincial People’s Hospital from February 2018 to November 2020 were retrospectively analyzed. All patients received platinum doublet chemotherapy for at least 2 cycles. CYFRA21-1 and CEA levels of patients were detected before and after the first chemotherapy cycle, respectively. After the second cycle, the efficacy was evaluated, and patients were divided into the disease control (DC) and progressive disease (PD) groups. The generalized linear model (GLM) and linear trend test assessed the relationship between change rates of CYFRA21-1 and CEA levels and chemotherapeutic efficacy before and after chemotherapy. Moreover, the receiver operating characteristic (ROC) curve determined the predictive value of change rates of CYFRA21-1 and CEA on chemotherapeutic efficacy. Results. After the second chemotherapeutic cycle, there were 92 patients in the DC group and 11 in the PD group. GLM and linear trend test both indicated that change rates of CYFRA21-1 and CEA were inversely correlated with chemotherapeutic efficacy for NSCLC. Change rates of CYFRA21-1 and CEA were used to predict area under the ROC curve of chemotherapeutic efficacy (0.87, 0.71-1.00), which is better than single index prediction of CYFRA21-1 (0.71, 0.49-0.94) or CEA change rate (0.85, 0.69-1.00) ( p < 0.001 ). Conclusion. Before and after chemotherapy of the first cycle for advanced NSCLC patients, combining serum CYFRA21-1 and CEA levels could increase sensitivity and specificity to predict the chemotherapeutic efficacy and guide the following therapy of advanced NSCLC patients.
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Amorim, Patrícia, Miguel Figueiredo, Miguel Machete, Telmo Morato, Ana Martins, and Ricardo Serrão Santos. "Spatial variability of seabird distribution associated with environmental factors: a case study of marine Important Bird Areas in the Azores." ICES Journal of Marine Science 66, no. 1 (November 5, 2008): 29–40. http://dx.doi.org/10.1093/icesjms/fsn175.
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Abstract Amorim, P., Figueiredo, M., Machete, M., Morato, T., Martins, A., and Serrão Santos, R. 2009. Spatial variability of seabird distribution associated with environmental factors: a case study of marine Important Bird Areas in the Azores. – ICES Journal of Marine Science, 66: 29–40. The spatial structure and distribution at sea of Cory's shearwaters (Calonectris diomedea borealis), common terns (Sterna hirundo), and roseate terns (Sterna dougallii) were analysed in the Azores for various environmental factors: sea surface temperature, chlorophyll a concentration, distance to fronts, wind, distance to island shore or tern colonies, distance to seamounts, seabed slope, and depth. Data on seabird sightings were collected by observers on board fishing vessels, 2002–2006. Generalized linear modelling (GLM) explained 43 and 11% of the abundance variability for terns (both species pooled) and Cory's shearwaters, respectively. Variability in seabird abundance was mainly explained by month, wind, distance to shore and/or tern colonies, and distance to seamounts. Variogram modelling indicated that species distribution presented a small-scale spatial structure (i.e. low autocorrelation). Cory's shearwater predictive distribution maps showed widespread distribution patterns of abundance, despite occurring at a greater intensity around the islands and around some seamounts, which are areas of fishery interest. Conversely, terns were essentially concentrated near the shore. The establishment of marine important bird areas should be encouraged close to seabird colonies and around some seamount areas.
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Kyei, Kwabena A. "Do parents Influence the Choice of Tertiary Institutions for their Children? Some Statistical Analyses." Journal of Economics and Behavioral Studies 7, no. 6(J) (December 30, 2015): 72–80. http://dx.doi.org/10.22610/jebs.v7i6(j).619.
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The paper investigates whether or not parents influence their children’s choice for tertiary institution to attend. Education has increasingly become more important in this present age to the extent that, without higher qualifications, employment and success become very difficult to achieve. Parents are trying to send their children to tertiary institutions so that these children will be employable. But the question is: Do parents choose the tertiary institutions for their children? The paper wants to find out whether or not parents have a say in their children’s choice for tertiary institution; and if so, look at factors that could play in the choice. A survey was conducted at the University of Venda from February 2015 to June 2015 and 500 students were conveniently sampled and interviewed. Using some statistical analyses, including Generalized Linear Modelling (GLM), the study concludes that age and the campus environment are the only factors that determine parents’ influence on their children’s choice for higher education. The study further shows that female students are more influenced by their parents than males in the choice of higher institution.
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DiGiacomo, Alexandra E., Walker E. Harrison, David W. Johnston, and Justin T. Ridge. "Elasmobranch Use of Nearshore Estuarine Habitats Responds to Fine-Scale, Intra-Seasonal Environmental Variation: Observing Coastal Shark Density in a Temperate Estuary Utilizing Unoccupied Aircraft Systems (UAS)." Drones 4, no. 4 (December 8, 2020): 74. http://dx.doi.org/10.3390/drones4040074.
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Many coastal shark species are known to use estuaries of the coastal southeastern United States for essential purposes like foraging, reproducing, and protection from predation. Temperate estuarine landscapes, such as the Rachel Carson Reserve (RCR) in Beaufort, NC, are dynamic habitat mosaics that experience fluctuations in physical and chemical oceanographic properties on various temporal and spatial scales. These patterns in abiotic conditions play an important role in determining species movement. The goal of this study was to understand the impact of environmental conditions around the RCR on shark density within the high-abundance summer season. Unoccupied Aircraft System (UAS) surveys of coastal habitats within the reserve were used to quantify shark density across varying environmental conditions. A combination of correlation analyses and Generalized Linear Modelling (GLM) revealed that density differs substantially across study sites and increases with rising water temperatures, conclusions that are supported by previous work in similar habitats. Additionally, density appears to increase moving towards dawn and dusk, potentially supporting crepuscular activity in coastal estuarine areas. By describing shark density dynamics in the RCR, this study provides new information on this population and presents a novel framework for studying elasmobranchs in temperate estuaries.
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Chen, Yuqing, Bruce Doran, Sharyn Sinclair-Hannocks, John Mangos, and Philip Gibbons. "Building selection by the common brushtail possum (Trichosurus vulpecula)." Wildlife Research 47, no. 2 (2020): 186. http://dx.doi.org/10.1071/wr19106.
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Abstract ContextThe common brushtail possum (Trichosurus vulpecula) is a protected native species in Australia that can access buildings in urban areas and cause considerable damage or disruption to building occupants. Although several strategies to discourage this species from entering buildings have been recommended, few have been evaluated empirically. AimsOur study aims to analyse how landscaping and building construction influence occupancy of buildings by the common brushtail possum. MethodsWe collated reports of possums occupying 134 buildings over 12 years on the campus of The Australian National University (ANU), in the Australian Capital Territory (ACT). We used generalised linear modelling (GLM) to identify associations between the total number of reported possum-related incidents for buildings and a range of landscape and building characteristics. Key resultsControlling for the effect of building size, we found that the number of reported possum-related incidents in buildings was positively associated with the percentage of tree and shrub canopy cover within the calculated home-range buffer distance of 49m from buildings, length of canopy overhanging roofs and building age, and negatively associated with tree species richness and number of trees with natural hollows and nest boxes within 49m of buildings. There were likely to be more possum-related reports from buildings in areas where the dominant tree genus was native, buildings with parapets (walls extending above the roof), buildings with structures penetrating from the roof, buildings with tile roofs and gable roofs. ConclusionsA combination of suitable habitat surrounding buildings, suitable access to the roofs of buildings and weak points in building roofs (e.g. parapets, roof penetrations), makes them more vulnerable to occupancy by the common brushtail possum. Implications Our results provided clues for managing existing buildings, or designing new buildings, in a way that may reduce the likelihood of occupancy by the common brushtail possum. Our study also demonstrated how building-maintenance records can be used to address human–wildlife conflict over time.
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Bedia, J., S. Herrera, and J. M. Gutiérrez. "Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System." Natural Hazards and Earth System Sciences Discussions 1, no. 5 (September 17, 2013): 4891–924. http://dx.doi.org/10.5194/nhessd-1-4891-2013.
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Abstract. We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990–2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter–annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.
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Martins, Inês, Miha Krofel, Paulo G. Mota, and Francisco Álvares. "Consumption of Carnivores by Wolves: A Worldwide Analysis of Patterns and Drivers." Diversity 12, no. 12 (December 11, 2020): 470. http://dx.doi.org/10.3390/d12120470.
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The occurrence of carnivore species in wolf diet has been overlooked and poorly studied despite the potential implications for wolf ecology and wildlife management. We conducted an extensive literature review, focusing on 120 wolf diet studies worldwide to assess global patterns of carnivore consumption by wolves and their ecological and human-related determinants. We used a total of 143 sampling sites with data on the consumption of carnivores by wolves. In total, 35 carnivore species were reported to be consumed by wolves, comprising members of all taxonomic carnivore families represented within the gray wolf range. The carnivores were mostly limited to occasional consumption (<5% of wolf diet) but could account for as much as 25% in some study areas. The most frequently consumed carnivore species were those with reported scavenging behavior, belonging to medium-sized generalist canids. Generalized linear model (GLM) analysis revealed that higher magnitudes of carnivore consumption were related to nonprotected areas as well as lower occurrences of wild ungulates, domestic ungulates, and small mammals in wolf diet, while higher numbers of consumed carnivore species were related to nonprotected areas with low vegetation productivity and lower occurrences of domestic ungulates and small mammals in wolf diet. Our results suggest that carnivore consumption by wolves is driven by altered ecosystems and human-dominated landscapes, where mesopredator densities are often increased and prey densities decreased, which intensify competition and the need for alternative food sources.
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Pellegrino, Irene, Luca Ilahiane, Giovanni Boano, Marco Cucco, Marco Pavia, Heather L. Prestridge, and Gary Voelker. "Avian Haemosporidian Diversity on Sardinia: A First General Assessment for the Insular Mediterranean." Diversity 13, no. 2 (February 10, 2021): 75. http://dx.doi.org/10.3390/d13020075.
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The Western Palearctic is one of the most investigated regions for avian haemosporidian parasites (Haemoproteus, Plasmodium and Leucocytozoon), yet geographic gaps in our regional knowledge remain. Here, we report the first haemosporidian screening of the breeding birds from Sardinia (the second-largest Mediterranean Island and a biodiversity hotspot), and the first for the insular Mediterranean in general. We examined the occurrence of haemosporidians by amplifying their mtDNA cytb gene in 217 breeding birds, belonging to 32 species. The total prevalence of infected birds was 55.3%, and of the 116 haplotypes recovered, 84 were novel. Despite the high number of novel lineages, phylogenetic analysis did not highlight Sardinia-specific clades; instead, some Sardinian lineages were more closely related to lineages previously recovered from continental Europe. Host-parasite network analysis indicated a specialized host-parasite community. Binomial generalized linear models (GLMs), performed at the community level, suggested an elevational effect on haemosporidian occurrence probability (negative for Haemoproteus; positive for Leucocytozoon) likely due to differences in the abundance of insect vectors at different elevations. Furthermore, a GLM revealed that sedentary birds showed a higher probability of being infected by novel haplotypes and long-distance migrants showed a lower probability of novel haplotype infection. We hypothesize that the high diversity of haemosporidians is linked to the isolation of breeding bird populations on Sardinia. This study adds to the growing knowledge on haemosporidians lineage diversity and distribution in insular environments and presents new insights on potential host-parasite associations.
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Harini, K., and K. Sashi Rekha. "Comparison of Logistic Regression and Generalized Linear Model for Identifying Accurate At – Risk Students." Alinteri Journal of Agriculture Sciences 36, no. 1 (June 22, 2021): 399–405. http://dx.doi.org/10.47059/alinteri/v36i1/ajas21060.
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Aim: To predict the accuracy percentage of At - risk students based on High withdrawal and Failure rate. Materials and methods: Logistic Regression with sample size = 20 and Generalised Linear Model (GLM) with sample size = 20 was iterated different times for predicting accuracy percentage of At - risk students. The Novel sigmoid function used in Logistic Regression maps prediction to probabilities which helps to improve the prediction of accuracy percentage. Results and Discussion: Logistic Regression has significantly better accuracy (94.48 %) compared to GLM accuracy (92.76 %). There was a statistical significance between Logistic regression and GLM (p=0.000) (p<0.05). Conclusion: Logistic Regression with Novel Sigmoid function helps in predicting with more accuracy percentage of At - risk students.
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Abdellatif, M., W. Atherton, and R. Alkhaddar. "A hybrid generalised linear and Levenberg–Marquardt artificial neural network approach for downscaling future rainfall in North Western England." Hydrology Research 44, no. 6 (January 16, 2013): 1084–101. http://dx.doi.org/10.2166/nh.2013.045.
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This paper describes a novel technique for downscaling daily rainfall which uses a combination of a generalised linear model (GLM) and artificial neural network (ANN) to downscale rainfall. A two-stage process is applied, an occurrence process which uses the GLM model and an amount process which uses an ANN model trained with a Levenberg–Marquardt approach. The GLM-ANN was compared with other three downscaling models, the traditional neural network (ANN), multiple linear regression (MLR) and Poisson regression (PR). The models are applied for downscaling daily rainfall at three locations in the North West of England during the winter and summer. Model performances with respect to reproduction of various statistics such as correlation coefficient, autocorrelation, root mean square errors (RMSE), standard deviation and the mean rainfall are examined. It is found that the GLM-ANN model performs better than the other three models in reproducing most daily rainfall statistics, with slight difficulties in predicting extremes rainfall event in summer. The GLM-ANN model is then used to project future rainfall at the three locations employing three different general circulation models (GCMs) for SRES scenarios A2 and B2. The study projects significant increases in mean daily rainfall at most locations for winter and decreases in summer.
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Thomas, Daniel B., Michael Kopp, and Katarina Markovič. "Using large-scale structure data and a halo model to constrain generalized dark matter." Monthly Notices of the Royal Astronomical Society 490, no. 1 (September 12, 2019): 813–31. http://dx.doi.org/10.1093/mnras/stz2559.
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ABSTRACT Constraints on the properties of the cosmological dark matter have previously been obtained in a model-independent fashion using the generalized dark matter (GDM) framework. Here we extend that work in several directions: We consider the inclusion of WiggleZ matter power spectrum data (MPS), and show that this improves the constraints on the two perturbative GDM parameters, $c^2_\mathrm{ s}$ and $c^2_\text{vis}$, by a factor of 3, for a conservative choice of wavenumber range. A less conservative choice can yield an improvement of up to an order of magnitude compared to previous constraints. In order to examine the robustness of this result we develop a GDM halo model (HM) to explore how non-linear structure formation could proceed in this framework, since currently GDM has only been defined perturbatively and only linear theory has been used when generating constraints. We then examine how the HM affects the constraints obtained from the MPS data. The less-conservative wavenumber range shows a significant difference between linear and non-linear modelling, with the latter favouring GDM parameters inconsistent with ΛCDM, underlining the importance of careful non-linear modelling when using this data. We also use this HM to establish the robustness of previously obtained constraints, particularly those that involve weak gravitational lensing of the cosmic microwave background. Additionally, we show how the inclusion of neutrino mass as a free parameter affects previous constraints on the GDM parameters.
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Perpetuini, David, Daniela Cardone, Chiara Filippini, Antonio Chiarelli, and Arcangelo Merla. "Modelling Impulse Response Function of Functional Infrared Imaging for General Linear Model Analysis of Autonomic Activity." Sensors 19, no. 4 (February 19, 2019): 849. http://dx.doi.org/10.3390/s19040849.
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Functional infrared imaging (fIRI) is a validated procedure to infer autonomic arousal. Currently, fIRI signals are analysed through descriptive metrics, such as average temperature changes in a region of interest (ROI). However, the employment of mathematical models could provide a powerful tool for the accurate identification of autonomic activity and investigation of the mechanisms underlying autonomic arousal. A linear temporal statistical model such as the general linear model (GLM) is particularly suited for its simplicity and direct interpretation. In order to apply the GLM, the thermal response linearity and time-invariance of fIRI have to be demonstrated, and the thermal impulse response (TIR) needs to be characterized. In this study, the linearity and time-invariance of the thermal response to sympathetic activating stimulation were demonstrated, and the TIR for employment of the GLM was characterized. The performance of the GLM-fIRI was evaluated by comparison with the GLM applied on synchronous measurements of the skin conductance response (SCR). In fact, the GLM-SCR is a validated procedure to estimate autonomic arousal. Assuming the GLM-SCR as the gold standard approach, a GLM-fIRI sensitivity and specificity of 86.4% and 75.9% were obtained. The GLM-fIRI may allow increased performances in the evaluation of autonomic activity and a broader range of application of fIRI in both research and clinical settings for the assessment of psychophysiological and psychopathological states.
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Khorozyan, Igor, Mahmood Soofi, Mobin Soufi, Amirhossein Khaleghi Hamidi, Arash Ghoddousi, and Matthias Waltert. "Effects of shepherds and dogs on livestock depredation by leopards (Panthera pardus) in north-eastern Iran." PeerJ 5 (February 23, 2017): e3049. http://dx.doi.org/10.7717/peerj.3049.
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Human-carnivore conflicts over livestock depredation are increasingly common, yet little is understood about the role of husbandry in conflict mitigation. As shepherds and guarding dogs are most commonly used to curb carnivore attacks on grazing livestock, evaluation and improvement of these practices becomes an important task. We addressed this issue by studying individual leopard (Panthera pardus) attacks on sheep and goats in 34 villages near Golestan National Park, Iran. We obtained and analyzed data on 39 attacks, which included a total loss of 31 sheep and 36 goats in 17 villages. We applied non-parametric testing, Poisson Generalized Linear Modelling (GLM) and model selection to assess how numbers of sheep and goats killed per attack are associated with the presence and absence of shepherds and dogs during attacks, depredation in previous years, villages, seasons, ethnic groups, numbers of sheep and goats kept in villages, and distances from villages to the nearest protected areas. We found that 95.5% of losses were inflicted in forests when sheep and goats were accompanied by shepherds (92.5% of losses) and dogs (77.6%). Leopards tended to kill more sheep and goats per attack (surplus killing) when dogs were absent in villages distant from protected areas, but still inflicted most losses when dogs were present, mainly in villages near protected areas. No other variables affected numbers of sheep and goats killed per attack. These results indicate that local husbandry practices are ineffectual and the mere presence of shepherds and guarding dogs is not enough to secure protection. Shepherds witnessed leopard attacks, but could not deter them while dogs did not exhibit guarding behavior and were sometimes killed by leopards. In an attempt to make practical, low-cost and socially acceptable improvements in local husbandry, we suggest that dogs are raised to create a strong social bond with livestock, shepherds use only best available dogs, small flocks are aggregated into larger ones and available shepherds herd these larger flocks together. Use of deterrents and avoidance of areas close to Golestan and in central, core areas of neighboring protected areas is also essential to keep losses down.
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Luiselli, Luca, Leonardo Sale, Godfrey C. Akani, and Giovanni Amori. "Venomous Snake Abundance Within Snake Species’ Assemblages Worldwide." Diversity 12, no. 2 (February 7, 2020): 69. http://dx.doi.org/10.3390/d12020069.
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Venomous snakes are among the main sources of mortality for humans in rural regions, especially in tropical countries. In this study, a meta-analysis of quantitative community ecology studies on snake assemblages throughout the world was conducted in order to evaluate variation in the frequency of occurrence of venomous species and venomous individuals by habitat and continent. A bibliographic search was done by consulting “Google Scholar” and “ISI Web of Knowledge”. In total, 24,200 results were obtained from our bibliographic search, out of which 60 independent studies reporting raw and analyzable quantitative data from 81 distinct snake communities were retained and used for analyses. A snow-ball procedure was also used to uncover additional studies to include in the analyses. We gathered data on a total of 30,537 snake individuals, with an average of almost 30% of venomous individuals. The mean number of sympatric species was 19, whereas the mean number of sympatric venomous species was almost 5. Venomous snake species accounted for 24.4% of the total species in each community—almost the same as the overall percentage of venomous snake species known worldwide (about 24%). The frequency of occurrence of venomous individuals did not differ significantly between tropical and temperate snake communities, and the same was true for the frequency of venomous species within each community. Thus, the greater number of snakebites in tropical countries is not due to there being more venomous snake species or individuals. The total number of species and the number of venomous species observed in each community were positively correlated, and there was a significant difference among continents in terms of the mean number of species in each community. Within communities, there were inter-continental and inter-habitat differences in both the percentage of venomous species and in the percentage of venomous individuals. The Generalized Linear Model (GLM) revealed that the frequency of venomous species at a local scale depended only on the total number of species inhabiting a given site, whereas the frequency of venomous individuals within communities depended on both the total number of species and a habitat–continent interaction. Our meta-analysis could enable the appropriate authorities/agencies to take the relative abundance of venomous species/individuals within snake assemblages into consideration for a better positioning of the first aid centers in locations where snake antivenoms should be available.
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Renshaw, A. E. "Actuarial graduation practice and generalised linear and non-linear models." Journal of the Institute of Actuaries 118, no. 2 (1991): 295–312. http://dx.doi.org/10.1017/s0020268100019454.
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ABSTRACTIt is demonstrated how existing actuarial graduation practice, used in the construction of life tables, can be extended to considerable effect by formulating the techniques within the generalised linear and non-linear modelling framework.
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Pitt, David, Jackie Li, and Tian Kang Lim. "SMOOTHING POISSON COMMON FACTOR MODEL FOR PROJECTING MORTALITY JOINTLY FOR BOTH SEXES." ASTIN Bulletin 48, no. 02 (January 9, 2018): 509–41. http://dx.doi.org/10.1017/asb.2017.44.
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AbstractWe consider a modification to the Poisson common factor model and utilise a generalised linear model (GLM) framework that incorporates a smoothing process and a set of linear constraints. We extend the standard GLM model structure to adopt Lagrange methods and P-splines such that smoothing and constraints are applied simultaneously as the parameters are estimated. Our results on Australian, Canadian and Norwegian data show that this modification results in an improvement in mortality projection in terms of producing more accurate forecasts in the out-of-sample testing. At the same time, projected male-to-female ratio of death rates at each age converges to a constant and the residuals of the models are sufficiently random, indicating that the use of smoothing does not adversely affect the fit of the model. Further, the irregular patterns in the estimates of the age-specific parameters are moderated as a result of smoothing and this model can be used to produce more regular projected life tables for pricing purposes.
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Rickard, J. M. "Application of a generalised linear modelling approach to category analysis." Transportation Planning and Technology 13, no. 2 (February 1989): 121–29. http://dx.doi.org/10.1080/03081068908717393.
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Jackson, Andrew S., Kenneth J. Ellis, Brian K. McFarlin, Mary H. Sailors, and Molly S. Bray. "Cross-validation of generalised body composition equations with diverse young men and women: the Training Intervention and Genetics of Exercise Response (TIGER) Study." British Journal of Nutrition 101, no. 6 (August 15, 2008): 871–78. http://dx.doi.org/10.1017/s0007114508047764.
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Generalised skinfold equations developed in the 1970s are commonly used to estimate laboratory-measured percentage fat (BF%). The equations were developed on predominately white individuals using Siri's two-component percentage fat equation (BF%-GEN). We cross-validated the Jackson–Pollock (JP) generalised equations with samples of young white, Hispanic and African–American men and women using dual-energy X-ray absorptiometry (DXA) as the BF% referent criterion (BF%-DXA). The cross-sectional sample included 1129 women and men (aged 17–35 years). The correlations between BF%-GEN and BF%-DXA were 0·85 for women and 0·93 for men. Analysis of measurement error showed that BF%-GEN underestimated BF%-DXA of men and women by 1·3 and 3·0 %. General linear models (GLM) confirmed that BF%-GEN systematically underestimated BF%-DXA of Hispanic men and women, and overestimated BF%-DXA of African–American men. GLM were used to estimate BF%-DXA from the JP sum of skinfolds and to account for race/ethnic group bias. The fit statistics (R and standard error of the estimate; see) of the men's calibration model were: white, R 0·92, see 3·0 %; Hispanic, R 0·91, see 3·0 %; African–American, R 0·95, see 2·6 %. The women's statistics were: white and African–American, R 0·86, see 3·8 %; Hispanic, R 0·83, see 3·4 %. These results showed that BF%-GEN and BF%-DXA were highly correlated, but the error analyses documented that the generalised equations lacked accuracy when applied to these racially and ethnically diverse men and women. The inaccuracy was linked to the body composition and race/ethnic differences between these Training Intervention and Genetics of Exercise Response (TIGER) study subjects and the men and women used to develop the generalised equations in the 1970s and using BF%-DXA as the referent criterion.
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Aufhauser, E., and M. M. Fischer. "Log-Linear Modelling and Spatial Analysis." Environment and Planning A: Economy and Space 17, no. 7 (July 1985): 931–51. http://dx.doi.org/10.1068/a170931.
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In the past decade the social sciences have seen an upsurge of interest in analysing multidimensional contingency tables using log-linear models. Two broad families of log-linear models may be distinguished: the family of conventional models and the family of unconventional models (that is, quasi-log-linear and hybrid models). In this paper a brief review of such models is presented and some linkage to the class of generalised linear models suggested by Nelder and Wedderburn is provided. The great potential of log-linear models for spatial analysis is illustrated in applying conventional and unconventional models in a migration context to identify intertemporal stability of migration patterns. The problem that the effective units migrating are households rather than individuals is coped with by postulating a compound Poisson sampling scheme.
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Michaelsen, Tore Christian. "Summer temperature and precipitation govern bat diversity at northern latitudes in Norway." Mammalia 80, no. 1 (January 1, 2016): 1–9. http://dx.doi.org/10.1515/mammalia-2014-0077.
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AbstractThis study investigated bat diversity in a temperature and precipitation gradient in fiord and valley landscapes of western Norway about 62° N. Equipment for automatic recording of bat calls was distributed in areas ranging from lowlands to alpine habitats with a mean July temperature range of 8–14°C. A general description of species distribution was given and diversity was analysed using both a generalised linear model (GLM) and a mixed-effects model (GLMM). With regard to the sampling design, the data were analysed on a binary scale, where presence or absence of any species other than the northern bat
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RICHES, NICK G. "Complex sentence profiles in children with Specific Language Impairment: Are they really atypical?" Journal of Child Language 44, no. 2 (February 15, 2016): 269–96. http://dx.doi.org/10.1017/s0305000915000847.
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AbstractChildren with Specific Language Impairment (SLI) have language difficulties of unknown origin. Syntactic profiles are atypical, with poor performance on non-canonical structures, e.g. object relatives, suggesting a localized deficit. However, existing analyses using ANOVAs are problematic because they do not systematically address unequal variance, or fully model random effects. Consequently, a Generalised Linear Model (GLM) was used to analyze data from a Sentence Repetition (SR) task involving relative clauses. seventeen children with SLI (mean age 6;7), twenty-one Language Matched (LM) children (mean age 4;8), and seventeen Age Matched (AM) children (mean age 6;5) repeated 100 canonical and non-canonical sentences. ANOVAs found a significant Group by Canonicity interaction for the SLI versus AM contrast only. However, the GLM found no significant interaction. Consequently, arguments for a localized deficit may depend on statistical methods which are prone to exaggerate profile differences. Nonetheless, a subgroup of SLI exhibited particularly severe structural language difficulties.
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Bučas, M., U. Bergström, A.-L. Downie, G. Sundblad, M. Gullström, M. von Numers, A. Šiaulys, and M. Lindegarth. "Empirical modelling of benthic species distribution, abundance, and diversity in the Baltic Sea: evaluating the scope for predictive mapping using different modelling approaches." ICES Journal of Marine Science 70, no. 6 (May 19, 2013): 1233–43. http://dx.doi.org/10.1093/icesjms/fst036.
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Abstract Bučas, M., Bergström, U., Downie, A-L., Sundblad, G., Gullström, M., von Numers, M., Šiaulys, A., and Lindegarth, M. 2013. Empirical modelling of benthic species distribution, abundance, and diversity in the Baltic Sea: evaluating the scope for predictive mapping using different modelling approaches. – ICES Journal of Marine Science, 70: 1233–1243. The predictive performance of distribution models of common benthic species in the Baltic Sea was compared using four non-linear methods: generalized additive models (GAMs), multivariate adaptive regression splines, random forest (RF), and maximum entropy modelling (MAXENT). The effects of data traits were also tested. In total, 292 occurrence models and 204 quantitative (abundance and diversity) models were assessed. The main conclusions are that (i) the spatial distribution, abundance, and diversity of benthic species in the Baltic Sea can be successfully predicted using several non-linear predictive modelling techniques; (ii) RF was the most accurate method for both models, closely followed by GAM and MAXENT; (iii) correlation coefficients of predictive performance among the modelling techniques were relatively low, suggesting that the performance of methods is related to specific responses; (iv) the differences in predictive performance among the modelling methods could only partly be explained by data traits; (v) the response prevalence was the most important explanatory variable for predictive accuracy of GAM and MAXENT on occurrence data; (vi) RF on the occurrence data was the only method sensitive to sampling density; (vii) a higher predictive accuracy of abundance models could be achieved by reducing variance in the response data and increasing the sample size.
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Stanton, Michelle C., and Peter J. Diggle. "Geostatistical analysis of binomial data: generalised linear or transformed Gaussian modelling?" Environmetrics 24, no. 3 (April 2, 2013): 158–71. http://dx.doi.org/10.1002/env.2205.
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Otieno, Odhiambo Luther, and Sam Ngwenya. "The relationship between capital structure and financial performance of firms listed on the Nairobi securities exchange." Corporate Ownership and Control 13, no. 1 (2015): 296–314. http://dx.doi.org/10.22495/cocv13i1c2p8.
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Until now, researchers are not in consensus, whether it is the capital structure that influences performance or performance that influences capital structure or both. The main objective of this study was to establish the relationship between capital structure and financial performance of firms listed on the NSE by employing a generalised linear model (GLM) as an improvement on ordinary least regression (OLS). The results of the study revealed that efficient and profitable firms employ more debt than comparable firms that are less profitable possibly because profitable firms’ exposure to financial risk is low. There results also indicate that firms that use more debt outperformed those that use less debt.
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Chandler, Richard E. "Multisite, multivariate weather generation based on generalised linear models." Environmental Modelling & Software 134 (December 2020): 104867. http://dx.doi.org/10.1016/j.envsoft.2020.104867.
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BISSELL, J. J., C. C. S. CAIADO, M. GOLDSTEIN, and B. STRAUGHAN. "COMPARTMENTAL MODELLING OF SOCIAL DYNAMICS WITH GENERALISED PEER INCIDENCE." Mathematical Models and Methods in Applied Sciences 24, no. 04 (January 28, 2014): 719–50. http://dx.doi.org/10.1142/s0218202513500656.
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A generalised compartmental method for investigating the spread of socially determined behaviour is introduced, and cast in the specific context of societal smoking dynamics with multiple peer influence. We consider how new peer influence terms, acting in both the rate at which smokers abandon their habit, and the rate at which former smokers relapse, can affect the spread of smoking in populations of constant size. In particular, we develop a three-population model (comprising classes of potential, current, and former smokers) governed by multiple incidence transfer rates with linear frequency dependence. Both a deterministic system and its stochastic analogue are discussed: in the first we demonstrate that multiple peer influence not only modifies the number of steady-states and nature of their asymptotic stability, but also introduces a new kind of non-linear "tipping-point" dynamic; while in the second we use recently compiled smoking statistics from the Northeast of England to investigate the impact of systemic uncertainty on the potential for societal "tipping". The generality of our assumptions mean that the results presented here are likely to be relevant to other compartmental models, especially those concerned with the transmission of socially determined behaviours.
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Koo, Ja-Yong, and Youngjo Lee. "Bivariate B-splines in generalised linear models." Journal of Statistical Computation and Simulation 50, no. 1-2 (August 1994): 119–29. http://dx.doi.org/10.1080/00949659408811603.
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Lovick, A. C., and P. K. W. Lee. "Redefining the deviance objective for generalised linear models." British Actuarial Journal 17, no. 3 (September 2012): 491–509. http://dx.doi.org/10.1017/s1357321712000190.
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AbstractThis paper defines the ‘Case Deleted’ Deviance - a new objective function for evaluating Generalised Linear Models, and applies this to a number of practical examples in the pricing of general insurance. The paper details practical approximations to enable the efficient calculation of the objective, and derives modifications to the standard Generalised Linear Modelling algorithm to allow the derivation of scaled parameters from this measure to reduce potential over fitting to historical data. These scaled parameters improve the predictiveness of the model when applied to previously unseen data points, the most likely being related to future business written. The potential for over fitting has increased due to number of factors now used, particularly in pricing personal lines business and the advent of price comparison sites which has increased the penalties of mis-estimation. New material in this paper has been included in a UK patent application No. 1020091.3.
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Atkinson, P. M., and R. Massari. "GENERALISED LINEAR MODELLING OF SUSCEPTIBILITY TO LANDSLIDING IN THE CENTRAL APENNINES, ITALY." Computers & Geosciences 24, no. 4 (May 1998): 373–85. http://dx.doi.org/10.1016/s0098-3004(97)00117-9.
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Ellem, B. A., A. Bryant, and A. O’Connor. "Statistical Modelling of Platypus, Ornithorhynchus anatinus, Habitat Preferences Using Generalised Linear Models." Australian Mammalogy 20, no. 2 (1998): 281. http://dx.doi.org/10.1071/am98281.
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Bryant (1993) collected extensive data on the habitat preferences of the platypus (Ornithorhynchus anatinus) measured in 36 pools in the upper Macquarie River system. Platypus presence or absence in these pools was measured on three occasions. Detailed modelling of the factors affecting pool preference was complicated by the scale of response being ordinal due to the inability of the observer to distinguish between repeated sightings of the same animal and several different animals. Initial modelling using logistic regression on a presence/absence index, collapsed from the ordinal response, discounted time of day and seasonal effects. These temporal simplifications allowed a binomial analysis of success rate based on the three visits, which identified an additional habitat factor not identified in the original analysis. Finally, a full ordinal regression of the proportions falling into each ordered category is presented as the ultimate modelling of platypus pooI preferences. The analysis indicated that length and depth of pools and the presence of overhanging vegetation were positively related to the observed presence of platypuses.
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Hilton, Jason, Erengul Dodd, Jonathan J. Forster, and Peter W. F. Smith. "Modelling Frontier Mortality Using Bayesian Generalised Additive Models." Journal of Official Statistics 37, no. 3 (September 1, 2021): 569–89. http://dx.doi.org/10.2478/jos-2021-0026.
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Abstract Mortality rates differ across countries and years, and the country with the lowest observed mortality has changed over time. However, the classic Science paper by Oeppen and Vaupel (2002) identified a persistent linear trend over time in maximum national life expectancy. In this article, we look to exploit similar regularities in age-specific mortality by considering for any given year a hypothetical mortality ‘frontier’, which we define as the lower limit of the force of mortality at each age across all countries. Change in this frontier reflects incremental advances across the wide range of social, institutional and scientific dimensions that influence mortality. We jointly estimate frontier mortality as well as mortality rates for individual countries. Generalised additive models are used to estimate a smooth set of baseline frontier mortality rates and mortality improvements, and country-level mortality is modelled as a set of smooth, positive deviations from this, forcing the mortality estimates for individual countries to lie above the frontier. This model is fitted to data for a selection of countries from the Human Mortality Database (2019). The efficacy of the model in forecasting over a ten-year horizon is compared to a similar model fitted to each country separately.
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Farza, Mondher, Mohammed M'Saad, Fenglong Liu, and Boubekeur Targui. "Generalised observers for a class of non-linear systems." International Journal of Modelling, Identification and Control 2, no. 1 (2007): 24. http://dx.doi.org/10.1504/ijmic.2007.014324.
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Green, Bridget S., Caleb Gardner, and Robert B. Kennedy. "Generalised linear modelling of fecundity at length in southern rock lobsters, Jasus edwardsii." Marine Biology 156, no. 9 (May 31, 2009): 1941–47. http://dx.doi.org/10.1007/s00227-009-1226-x.
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