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Journal articles on the topic 'Generalised smoothing'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Pizarro, Luis, Pavel Mrázek, Stephan Didas, Sven Grewenig, and Joachim Weickert. "Generalised Nonlocal Image Smoothing." International Journal of Computer Vision 90, no. 1 (April 9, 2010): 62–87. http://dx.doi.org/10.1007/s11263-010-0337-7.

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2

Osborne, M. R., and Tania Prvan. "On algorithms for generalised smoothing splines." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 29, no. 3 (January 1988): 322–41. http://dx.doi.org/10.1017/s0334270000005841.

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AbstractRecently, considerable interest has been shown in the connection between smoothing splines and a particular class of stochastic processes. Here the connection with an equivalent class of least squares problems is used to develop algorithms, and properties of the solution are examined. We give an estimate of the condition number of the solution process and compare this with an estimate for the condition number of the Reinsch algorithm in its conventional implementation.

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3

Osborne, M. R., and Tania Prvan. "Smoothness and conditioning in generalised smoothing spline calculations." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 30, no. 1 (July 1988): 43–56. http://dx.doi.org/10.1017/s0334270000006020.

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AbstractWe consider a generalisation of the stochastic formulation of smoothing splines, and discuss the smoothness properties of the resulting conditional expectation (generalised smoothing spline), and the sensitivity of the numerical algorithms. One application is to the calculation of smoothing splines with less than the usual order of continuity at the data points.

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4

Friston, Karl, Klaas Stephan, Baojuan Li, and Jean Daunizeau. "Generalised Filtering." Mathematical Problems in Engineering 2010 (2010): 1–34. http://dx.doi.org/10.1155/2010/621670.

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We describe a Bayesian filtering scheme for nonlinear state-space models in continuous time. This scheme is called Generalised Filtering and furnishes posterior (conditional) densities on hidden states and unknown parameters generating observed data. Crucially, the scheme operates online, assimilating data to optimize the conditional density on time-varying states and time-invariant parameters. In contrast to Kalman and Particle smoothing, Generalised Filtering does not require a backwards pass. In contrast to variational schemes, it does not assume conditional independence between the states and parameters. Generalised Filtering optimises the conditional density with respect to a free-energy bound on the model's log-evidence. This optimisation uses the generalised motion of hidden states and parameters, under the prior assumption that the motion of the parameters is small. We describe the scheme, present comparative evaluations with a fixed-form variational version, and conclude with an illustrative application to a nonlinear state-space model of brain imaging time-series.

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5

Lu, Yiqiang, and Riquan Zhang. "Smoothing spline estimation of generalised varying-coefficient mixed model." Journal of Nonparametric Statistics 21, no. 7 (October 2009): 815–25. http://dx.doi.org/10.1080/10485250903151078.

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6

Chaubey, Yogendra P., Naâmane Laïb, and Arusharka Sen. "Generalised kernel smoothing for non-negative stationary ergodic processes." Journal of Nonparametric Statistics 22, no. 8 (November 2010): 973–97. http://dx.doi.org/10.1080/10485251003605120.

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7

Troudi, Molka, and Faouzi Ghorbel. "The Generalised Plug-in Algorithm for the Diffeomorphism Kernel Estimate." International Journal of Mathematics and Computers in Simulation 15 (November 27, 2021): 128–33. http://dx.doi.org/10.46300/9102.2021.15.24.

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The optimal value of the smoothing parameter of the Kernel estimator can be obtained by the well known Plug-in algorithm. The optimality is realised in the sense of Mean Integrated Square Error (MISE). In this paper, we propose to generalise this algorithm to the case of the difficult problem of the estimation of a distribution which has a bounded support. The proposed algorithm consists in searching the optimal smoothing parameter by iterations from the expression of MISE of the kernel-diffeomorphism estimator. By some simulations applied to some distribution having a support bounded and semi bounded, we show that the support of the pdf estimator respects the one of the theoretical distribution. We also prove that the proposed method minimizes the Gibbs phenomenon.

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8

Liu, Yaping. "Smoothing the domain out for positive solutions." Bulletin of the Australian Mathematical Society 61, no. 3 (June 2000): 405–13. http://dx.doi.org/10.1017/s0004972700022437.

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For a given nonlinear partial differential equation defined on a bounded domain with irregular boundary, the available analytical tools are very limited in relation to the study of positive solutions. In this paper wer first use weak convergence methods to show that for an elliptic equation of a certain type, classical positive solutions on nearby smooth domains approach a generalised positive solution on the given domain. The idea is then applied to sublinear elliptic problems to obtain existence and uniqueness results.

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9

Hancock, P. A., and M. F. Hutchinson. "An iterative procedure for calculating minimum generalised cross validation smoothing splines." ANZIAM Journal 44 (April 1, 2003): 290. http://dx.doi.org/10.21914/anziamj.v44i0.683.

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10

Ombao, H. C., J. A. Raz, R. L. Strawderman, and R. Von Sachs. "A simple generalised crossvalidation method of span selection for periodogram smoothing." Biometrika 88, no. 4 (December 1, 2001): 1186–92. http://dx.doi.org/10.1093/biomet/88.4.1186.

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11

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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12

Laroussi, Ilhem. "A generalised censored least squares and smoothing spline estimators of regression function." International Journal of Mathematics in Operational Research 20, no. 4 (2021): 506. http://dx.doi.org/10.1504/ijmor.2021.120102.

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13

Tan, Jun, and Zaiping Nie. "Polarisation smoothing generalised MUSIC algorithm with PSA monostatic MIMO radar for low angle estimation." Electronics Letters 54, no. 8 (April 2018): 527–29. http://dx.doi.org/10.1049/el.2017.4378.

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14

Chu, Fengkui, Hong Li, Jian Wen, and Mingquan Lu. "Statistical Model and Performance Evaluation of a GNSS Spoofing Detection Method based on the Consistency of Doppler and Pseudorange Positioning Results." Journal of Navigation 72, no. 2 (October 25, 2018): 447–66. http://dx.doi.org/10.1017/s0373463318000747.

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Global Navigation Satellite System (GNSS) safety issues of have been of concern for some time. Spoofing attacks have received much attention as they can be difficult to detect and have the potential to cause disruption at best and major damage in extremis. To mitigate such threats, a spoofing detection method based on the consistency check of Doppler positioning fixes and pseudorange positioning fixes is proposed. The primary contributions of this paper include establishing a Generalised Likelihood Ratio Test (GLRT)-based statistical detection model for the introduced spoofing detection method and efficiently improving the accuracy of the Doppler positioning method as well as the performance of the detection approach by a modified α-filter-based Doppler smoothing technique. Theoretical performance of the proposed detection model is analysed. Monte Carlo simulations were also conducted to verify the theoretical analysis. Moreover, grounded on the developed test statistic and the optimised threshold, a consistency check module was specifically realised in both software defined and real-time GNSS receivers. Additionally, a Doppler smoothing technique was applied to the receivers. Spoofing attack experiments on both software defined and real-time platforms validated the effectiveness of the statistical spoofing detection model.

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15

Rodríguez-Álvarez, María Xosé, Maria Durban, Dae-Jin Lee, and Paul H. C. Eilers. "On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing." Statistics and Computing 29, no. 3 (June 11, 2018): 483–500. http://dx.doi.org/10.1007/s11222-018-9818-2.

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16

Courtial, Azelle, Achraf El Ayedi, Guillaume Touya, and Xiang Zhang. "Exploring the Potential of Deep Learning Segmentation for Mountain Roads Generalisation." ISPRS International Journal of Geo-Information 9, no. 5 (May 25, 2020): 338. http://dx.doi.org/10.3390/ijgi9050338.

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Among cartographic generalisation problems, the generalisation of sinuous bends in mountain roads has always been a popular one due to its difficulty. Recent research showed the potential of deep learning techniques to overcome some remaining research problems regarding the automation of cartographic generalisation. This paper explores this potential on the popular mountain road generalisation problem, which requires smoothing the road, enlarging the bend summits, and schematising the bend series by removing some of the bends. We modelled the mountain road generalisation as a deep learning problem by generating an image from input vector road data, and tried to generate it as an output of the model a new image of the generalised roads. Similarly to previous studies on building generalisation, we used a U-Net architecture to generate the generalised image from the ungeneralised image. The deep learning model was trained and evaluated on a dataset composed of roads in the Alps extracted from IGN (the French national mapping agency) maps at 1:250,000 (output) and 1:25,000 (input) scale. The results are encouraging as the output image looks like a generalised version of the roads and the accuracy of pixel segmentation is around 65%. The model learns how to smooth the output roads, and that it needs to displace and enlarge symbols but does not always correctly achieve these operations. This article shows the ability of deep learning to understand and manage the geographic information for generalisation, but also highlights challenges to come.

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17

Luati, Alessandra, and Tommaso Proietti. "On the equivalence of the weighted least squares and the generalised least squares estimators, with applications to kernel smoothing." Annals of the Institute of Statistical Mathematics 63, no. 4 (November 3, 2009): 851–71. http://dx.doi.org/10.1007/s10463-009-0267-8.

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18

Skillen, Alex, Steven Lind, Peter K. Stansby, and Benedict D. Rogers. "Incompressible smoothed particle hydrodynamics (SPH) with reduced temporal noise and generalised Fickian smoothing applied to body–water slam and efficient wave–body interaction." Computer Methods in Applied Mechanics and Engineering 265 (October 2013): 163–73. http://dx.doi.org/10.1016/j.cma.2013.05.017.

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19

Theljani, Anis, and Ke Chen. "Diffeomorphic unsupervised deep learning model for mono- and multi-modality registration." Journal of Algorithms & Computational Technology 14 (January 2020): 174830262097352. http://dx.doi.org/10.1177/1748302620973528.

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Different from image segmentation, developing a deep learning network for image registration is less straightforward because training data cannot be prepared or supervised by humans unless they are trivial (e.g. pre-designed affine transforms). One approach for an unsupervised deep leaning model is to self-train the deformation fields by a network based on a loss function with an image similarity metric and a regularisation term, just with traditional variational methods. Such a function consists in a smoothing constraint on the derivatives and a constraint on the determinant of the transformation in order to obtain a spatially smooth and plausible solution. Although any variational model may be used to work with a deep learning algorithm, the challenge lies in achieving robustness. The proposed algorithm is first trained based on a new and robust variational model and tested on synthetic and real mono-modal images. The results show how it deals with large deformation registration problems and leads to a real time solution with no folding. It is then generalised to multi-modal images. Experiments and comparisons with learning and non-learning models demonstrate that this approach can deliver good performances and simultaneously generate an accurate diffeomorphic transformation.

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20

Fellner, Klemens, Evangelos Latos, and Bao Quoc Tang. "Global regularity and convergence to equilibrium of reaction–diffusion systems with nonlinear diffusion." Journal of Evolution Equations 20, no. 3 (October 17, 2019): 957–1003. http://dx.doi.org/10.1007/s00028-019-00543-3.

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Abstract We study the boundedness and convergence to equilibrium of weak solutions to reaction–diffusion systems with nonlinear diffusion. The nonlinear diffusion is of porous medium type, and the nonlinear reaction terms are assumed to grow polynomially and to dissipate (or conserve) the total mass. By utilising duality estimates, the dissipation of the total mass and the smoothing effect of the porous medium equation, we prove that if the exponents of the nonlinear diffusion terms are high enough, then weak solutions are bounded, locally Hölder continuous and their $$L^{\infty }(\Omega )$$ L ∞ ( Ω ) -norm grows in time at most polynomially. In order to show convergence to equilibrium, we consider a specific class of nonlinear reaction–diffusion models, which describe a single reversible reaction with arbitrarily many chemical substances. By exploiting a generalised logarithmic Sobolev inequality, an indirect diffusion effect and the polynomial in time growth of the $$L^{\infty }(\Omega )$$ L ∞ ( Ω ) -norm, we show an entropy–entropy production inequality which implies exponential convergence to equilibrium in $$L^p(\Omega )$$ L p ( Ω ) -norm, for any $$1\le p < \infty $$ 1 ≤ p < ∞ , with explicit rates and constants.

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21

Ilyash, Olha, Ruslan Lupak, Maryna Kravchenko, Olena Trofymenko, Natalia Duliaba, and Iryna Dzhadan. "A FORECASTING MODEL FOR ASSESSING THE INFLUENCE OF THE COMPONENTS OF TECHNOLOGICAL GROWTH ON ECONOMIC SECURITY." Business: Theory and Practice 23, no. 1 (April 19, 2022): 175–86. http://dx.doi.org/10.3846/btp.2022.15298.

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The system of indicators for assessing the impact of the components of technological growth on economic security is generalised. This task is carried out by selecting a system of indicators (40 indicators), which, on the one hand, are consistent with one another and with key indicators used in analysing the state of economic security, and which are identified by the components of technological development, on the other hand. The standardisation of the values of initial data i.e. indicators, the determination of the degree of their deviations from the reference parameters and further integral assessment helped to find a generalised indicator of the state of development and the influence of technological growth on the parameters of the system of economic security. The purpose of the study is to test tools for forecasting modelling of the results of assessing the impact of technological growth on economic security. In accordance with the purpose, the level of relationships between the indicators of technological growth and the level of economic security is assessed. High, average and low levels of their relationship is revealed. The obtained results made it possible to forecast the rates of technological growth, perform exponential smoothing of the forecast estimates of the impact of the components of technological growth on economic security and employ damping measurement of the forecast level of the dependence of technological growth and economic security. Taking into account trends in technological growth, the system of indicators of the forecasting model for assessing economic security is expanded. The accuracy of the forecast is determined by the limits of the analysed period of the dynamics of the indicators – from 2013 to 2019, considering the impact of changes in the methodology for calculating individual input data according to statistical sources for the period under study. The use of forecasting models to assess the impact of technological development on Ukraine’s economic security will help identify political, economic, social and technological factors that will stimulate investment, strengthen economic openness, increase the volume and share of domestic high-tech exports, and thus, strengthen economic security.

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22

García-Ligero, María Jesús, Aurora Hermoso-Carazo, and Josefa Linares-Pérez. "Distributed Fusion Estimation with Sensor Gain Degradation and Markovian Delays." Mathematics 8, no. 11 (November 4, 2020): 1948. http://dx.doi.org/10.3390/math8111948.

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This paper investigates the distributed fusion estimation of a signal for a class of multi-sensor systems with random uncertainties both in the sensor outputs and during the transmission connections. The measured outputs are assumed to be affected by multiplicative noises, which degrade the signal, and delays may occur during transmission. These uncertainties are commonly described by means of independent Bernoulli random variables. In the present paper, the model is generalised in two directions: (i) at each sensor, the degradation in the measurements is modelled by sequences of random variables with arbitrary distribution over the interval [0, 1]; (ii) transmission delays are described using three-state homogeneous Markov chains (Markovian delays), thus modelling dependence at different sampling times. Assuming that the measurement noises are correlated and cross-correlated at both simultaneous and consecutive sampling times, and that the evolution of the signal process is unknown, we address the problem of signal estimation in terms of covariances, using the following distributed fusion method. First, the local filtering and fixed-point smoothing algorithms are obtained by an innovation approach. Then, the corresponding distributed fusion estimators are obtained as a matrix-weighted linear combination of the local ones, using the mean squared error as the criterion of optimality. Finally, the efficiency of the algorithms obtained, measured by estimation error covariance matrices, is shown by a numerical simulation example.

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23

Rodríguez-Álvarez, María Xosé, Javier Roca-Pardiñas, Carmen Cadarso-Suárez, and Pablo G. Tahoces. "Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis." Statistical Methods in Medical Research 27, no. 3 (December 12, 2017): 740–64. http://dx.doi.org/10.1177/0962280217742542.

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Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analysed.

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24

Searle, K. R., A. Blackwell, D. Falconer, M. Sullivan, A. Butler, and B. V. Purse. "Identifying environmental drivers of insect phenology across space and time: Culicoides in Scotland as a case study." Bulletin of Entomological Research 103, no. 2 (July 30, 2012): 155–70. http://dx.doi.org/10.1017/s0007485312000466.

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AbstractInterpreting spatial patterns in the abundance of species over time is a fundamental cornerstone of ecological research. For many species, this type of analysis is hampered by datasets that contain a large proportion of zeros, and data that are overdispersed and spatially autocorrelated. This is particularly true for insects, for which abundance data can fluctuate from zero to many thousands in the space of weeks. Increasingly, an understanding of the ways in which environmental variation drives spatial and temporal patterns in the distribution, abundance and phenology of insects is required for management of pests and vector-borne diseases. In this study, we combine the use of smoothing techniques and generalised linear mixed models to relate environmental drivers to key phenological patterns of two species of biting midges, Culicoides pulicaris and C. impunctatus, of which C. pulicaris has been implicated in transmission of bluetongue in Europe. In so doing, we demonstrate analytical tools for linking the phenology of species with key environmental drivers, despite using a relatively small dataset containing overdispersed and zero-inflated data. We demonstrate the importance of landcover and climatic variables in determining the seasonal abundance of these two vector species, and highlight the need for more empirical data on the effects of temperature and precipitation on the life history traits of palearctic Culicoides spp. in Europe.

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25

Olaniyan, Temitayo Olumide. "Interactive Effects of Remittances and Financial Sector Development on Economic Growth in Nigeria." Remittances Review 4, no. 1 (May 28, 2019): 19–39. http://dx.doi.org/10.33182/rr.v4i1.677.

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A well-developed and efficient financial sector together with remittances can serve as a transmission mechanism to ensure well-rounded economic growth because extant literature shows that remittances alone may not be sufficient to promote the desirable level of economic growth. Therefore, this study investigated the interactive effects of remittances and financial sector development on economic growth in Nigeria for the period 1977-2017. The data for this study was obtained from the World Bank’s World Development Indicator (WDI) Database. The data were analysed using the Instrumental Variable Generalised Method of Moments (IV-GMM) estimator. The findings of this study showed that remittances alone had a negatively significant effect on economic growth at 1% significance level but when interacted with financial sector development, they enhance economic growth as revealed by the positive coefficient of the interactive term which is also significant at 1% level. The study concluded that Nigeria’s economy profits from migrants’ remittances in terms of economic growth through the existence of a developed financial sector. This study recommended among other things that the interaction of remittances and financial sector development should be used as an avenue to encourage more savings from remittances by lowering transaction costs and increasing payment of deposits’ interest on remitted funds. Besides, bank financial institutions should find a better match for these savings (in terms of investment opportunities) in order to neutralise the negative effects of remittances on economic growth caused by recipients’ consumption smoothing drive.

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26

Bahlmann, Edda, Eigir Einarsen, Dana Cramariuc, Helga Midtbø, Costantino Mancusi, Anne Rossebø, Stephan Willems, and Eva Gerdts. "Low myocardial energetic efficiency is associated with increased mortality in aortic stenosis." Open Heart 8, no. 2 (August 2021): e001720. http://dx.doi.org/10.1136/openhrt-2021-001720.

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ObjectivesIn hypertension, low myocardial energetic efficiency (MEEi) has been documented as an integrated marker of metabolic and left ventricular (LV) myocardial dysfunction. We tested the predictive performance of MEEi in initially asymptomatic aortic stenosis (AS) patients free from diabetes and known cardiovascular disease.MethodsData from 1703 patients with mostly moderate AS enrolled in the Simvastatin and Ezetimibe in Aortic Stenosis study followed for 4.3 years was used. MEE was calculated from Doppler stroke volume/([heart rate/60]) and indexed to LV mass (MEEi). The threshold value for MEEi associated with increased mortality was identified in generalised additive model with smoothing splines. Covariables of MEEi were identified in logistic regression analysis. Outcome was assessed in Cox regression analysis and reported as HR and 95% CI.ResultsMEEi <0.34 mL/s per gram was associated with increased cardiovascular mortality (n=80) (HR 2.53 (95% CI 1.50 to 4.28)) and all-cause mortality (n=155) (HR 1.74 (95% CI 1.20 to 2.52)) (both p<0.01). The association was independent of confounders of low MEEI (<0.34 mL/s per gram) identified in multivariable logistic regression analysis, including more severe AS, higher body mass index, lower LV midwall shortening and ejection fraction and presence of hypertension. Comparison of the Cox models with and without MEEi among the covariables demonstrated that MEEi significantly improved the prognostic yield (both p<0.01).ConclusionsIn patients with initially asymptomatic AS, low MEEi was associated with clustering of cardiometabolic risk factors, lower LV myocardial function and subsequent increased mortality during 4.3 years follow-up, independent of known prognosticators.Trial registration numberNCT00092677.

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27

Berzuini, Carlo, Cathal Hannan, Andrew King, Andy Vail, Claire O'Leary, David Brough, James Galea, et al. "Value of dynamic clinical and biomarker data for mortality risk prediction in COVID-19: a multicentre retrospective cohort study." BMJ Open 10, no. 9 (September 2020): e041983. http://dx.doi.org/10.1136/bmjopen-2020-041983.

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ObjectivesBeing able to predict which patients with COVID-19 are going to deteriorate is important to help identify patients for clinical and research practice. Clinical prediction models play a critical role in this process, but current models are of limited value because they are typically restricted to baseline predictors and do not always use contemporary statistical methods. We sought to explore the benefits of incorporating dynamic changes in routinely measured biomarkers, non-linear effects and applying ‘state-of-the-art’ statistical methods in the development of a prognostic model to predict death in hospitalised patients with COVID-19.DesignThe data were analysed from admissions with COVID-19 to three hospital sites. Exploratory data analysis included a graphical approach to partial correlations. Dynamic biomarkers were considered up to 5 days following admission rather than depending solely on baseline or single time-point data. Marked departures from linear effects of covariates were identified by employing smoothing splines within a generalised additive modelling framework.Setting3 secondary and tertiary level centres in Greater Manchester, the UK.Participants392 hospitalised patients with a diagnosis of COVID-19.Results392 patients with a COVID-19 diagnosis were identified. Area under the receiver operating characteristic curve increased from 0.73 using admission data alone to 0.75 when also considering results of baseline blood samples and to 0.83 when considering dynamic values of routinely collected markers. There was clear non-linearity in the association of age with patient outcome.ConclusionsThis study shows that clinical prediction models to predict death in hospitalised patients with COVID-19 can be improved by taking into account both non-linear effects in covariates such as age and dynamic changes in values of biomarkers.

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Clark, Nicholas J., Tatiana Proboste, Guyan Weerasinghe, and Ricardo J. Soares Magalhães. "Near-term forecasting of companion animal tick paralysis incidence: An iterative ensemble model." PLOS Computational Biology 18, no. 2 (February 16, 2022): e1009874. http://dx.doi.org/10.1371/journal.pcbi.1009874.

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Tick paralysis resulting from bites from Ixodes holocyclus and I. cornuatus is one of the leading causes of emergency veterinary admissions for companion animals in Australia, often resulting in death if left untreated. Availability of timely information on periods of increased risk can help modulate behaviors that reduce exposures to ticks and improve awareness of owners for the need of lifesaving preventative ectoparasite treatment. Improved awareness of clinicians and pet owners about temporal changes in tick paralysis risk can be assisted by ecological forecasting frameworks that integrate environmental information into statistical time series models. Using an 11-year time series of tick paralysis cases from veterinary clinics in one of Australia’s hotspots for the paralysis tick Ixodes holocyclus, we asked whether an ensemble model could accurately forecast clinical caseloads over near-term horizons. We fit a series of statistical time series (ARIMA, GARCH) and generative models (Prophet, Generalised Additive Model) using environmental variables as predictors, and then combined forecasts into a weighted ensemble to minimise prediction interval error. Our results indicate that variables related to temperature anomalies, levels of vegetation moisture and the Southern Oscillation Index can be useful for predicting tick paralysis admissions. Our model forecasted tick paralysis cases with exceptional accuracy while preserving epidemiological interpretability, outperforming a field-leading benchmark Exponential Smoothing model by reducing both point and prediction interval errors. Using online particle filtering to assimilate new observations and adjust forecast distributions when new data became available, our model adapted to changing temporal conditions and provided further reduced forecast errors. We expect our model pipeline to act as a platform for developing early warning systems that can notify clinicians and pet owners about heightened risks of environmentally driven veterinary conditions.

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29

Kawakatsu, Yoshito, Christopher Adolph, Jonathan F. Mosser, Peter Baffoe, Fatima Cheshi, Hirotsugu Aiga, David Watkins, and Kenneth H. Sherr. "Factors consistently associated with utilisation of essential maternal and child health services in Nigeria: analysis of the five Nigerian national household surveys (2003–2018)." BMJ Open 12, no. 9 (September 2022): e061747. http://dx.doi.org/10.1136/bmjopen-2022-061747.

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ObjectiveThis study aims to identify the individual and contextual factors consistently associated with utilisation of essential maternal and child health services in Nigeria across time and household geolocation.Design, setting and participantsSecondary data from five nationally representative household surveys conducted in Nigeria from 2003 to 2018 were used in this study. The study participants are women and children depending on essential maternal and child health (MCH) services.Outcome measuresThe outcome measures were indicators of whether participants used each of the following essential MCH services: antenatal care, facility-based delivery, modern contraceptive use, childhood immunisations (BCG, diphtheria, tetanus, pertussis/Pentavalent and measles) and treatments of childhood illnesses (fever, cough and diarrhoea).MethodsWe estimated generalised additive models with logit links and smoothing terms for households’ geolocation and survey years.ResultsHigher maternal education and households’ wealth were significantly associated with utilisation of all types of essential MCH services (p<0.05). On the other hand, households with more children under 5 years of age and in poor communities were significantly less likely to use essential MCH services (p<0.05). Except for childhood immunisations, greater access to transport was positively associated with utilisation (p<0.05). Households with longer travel times to the most accessible health facility were less likely to use all types of essential MCH services (p<0.05), except modern contraceptive use and treatment of childhood fever and/or cough.ConclusionThis study adds to the evidence that maternal education and household wealth status are consistently associated with utilisation of essential MCH services across time and space. To increase utilisation of essential MCH services across different geolocations, interventions targeting poor communities and households with more children under 5 years of age should be appropriately designed. Moreover, additional interventions should prioritise to reduce inequities of essential MCH service utilisation between the wealth quantiles and between education status.

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Herkenrath, Ulrich. "Generalized adaptive exponential smoothing procedures." Journal of Applied Probability 31, no. 3 (September 1994): 673–90. http://dx.doi.org/10.2307/3215147.

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The classical exponential smoothing procedure to be applied to a sequence of observations is modified into some adaptive variants and also generalized to the recursive schemeThis means that given the history of observations and smoothed values up to time n, the updated smoothed value Wn +1 is given by a function u of Wn and Xn, which satisfies only certain structural properties. We study these procedures within the framework of random systems with complete connections and exploit results from Markov process theory to study the sequence . A broad class of ‘smoothing functions' u, which induce sequences with nice statistical properties, is presented. A method to estimate the limit of the expected smoothed values is also developed.,

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Niedzwiecki, M. "Generalized Adaptive Notch Smoothing Revisited." IEEE Transactions on Signal Processing 58, no. 3 (March 2010): 1565–76. http://dx.doi.org/10.1109/tsp.2009.2037071.

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Herkenrath, Ulrich. "Generalized adaptive exponential smoothing procedures." Journal of Applied Probability 31, no. 03 (September 1994): 673–90. http://dx.doi.org/10.1017/s0021900200045253.

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The classical exponential smoothing procedure to be applied to a sequence of observations is modified into some adaptive variants and also generalized to the recursive scheme This means that given the history of observations and smoothed values up to time n, the updated smoothed value Wn + 1 is given by a function u of Wn and Xn , which satisfies only certain structural properties. We study these procedures within the framework of random systems with complete connections and exploit results from Markov process theory to study the sequence . A broad class of ‘smoothing functions' u, which induce sequences with nice statistical properties, is presented. A method to estimate the limit of the expected smoothed values is also developed.,

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33

Granek, H. "Generalized smoothing splines in CO2analysis." Journal of Geophysical Research 100, no. D8 (1995): 16857. http://dx.doi.org/10.1029/95jd00562.

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Asmuss, Svetlana, and Natalja Budkina. "ON SOME GENERALIZATION OF SMOOTHING PROBLEMS." Mathematical Modelling and Analysis 20, no. 3 (June 2, 2015): 311–28. http://dx.doi.org/10.3846/13926292.2015.1048756.

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The paper deals with the generalized smoothing problem in abstract Hilbert spaces. This generalized problem involves particular cases such as the interpolating problem, the smoothing problem with weights, the smoothing problem with obstacles, the problem on splines in convex sets and others. The theorem on the existence and characterization of a solution of the generalized problem is proved. It is shown how the theorem gives already known theorems in special cases as well as some new results.

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Wang, Jian, LingLing Shen, LeSheng Jin, and Gang Qian. "Age Sequence Recursive Models for Long Time Evaluation Problems." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, no. 02 (April 2018): 299–325. http://dx.doi.org/10.1142/s0218488518500162.

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The evaluation models for long time historical data is important in many applications. In this study, based on Age measure defined by Yager, we propose the definitions of Age Sequence and Age Series. Then, we provide a Generalized Recursive Smoothing method. Some classical smoothing models in evaluation problems can be seen as special cases of Generalized Recursive Smoothing method. In order to obtain more reasonable and effective aggregation results of the historical data, we propose some different Age Sequences, e.g., the Generalized Harmonic Age Sequence and p Age Sequence, which theoretically can provide infinite more recursive smoothing methods satisfying different preferences of decision makers.

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Pescott, Oliver L., Thomas A. Humphrey, Peter A. Stroh, and Kevin J. Walker. "Temporal changes in distributions and the species atlas: How can British and Irish plant data shoulder the inferential burden?" British & Irish Botany 1, no. 4 (December 14, 2019): 250–82. http://dx.doi.org/10.33928/bib.2019.01.250.

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Species distribution atlases often rely on volunteer effort to achieve their desired coverage, an activity now typically discussed, at least in academia, under the general theme of “citizen science”. Such data, however, are rarely without complex biases, particularly with respect to the estimation of trends in species’ distributions over many decades. The data of the Botanical Society of Britain and Ireland (BSBI) are no exception to this, and both careful thought in data aggregation (spatial, temporal, and taxonomic) and appropriate modelling procedures are required to overcome these challenges. We discuss these issues, with a primary focus on the statistical models that have been put forward to adjust for such biases. Such models include the Telfer method, various “reporting rate” approaches based on generalised linear models, the frequency scaling using local occupancy (“Frescalo”) model, occupancy models, and spatial smoothing methods. In each case the strengths and limitations in relation to estimating trends from distribution data with important time-varying biases are assessed. Various properties of BSBI data, in particular the increasing numbers of records at fine spatial and temporal scales over the past century, coupled with a general lack of re-visits to sites at such finer scales and the time-varying biases previously mentioned, imply that methods that can be sensibly applied at coarser levels are likely to be most appropriate for estimating accurate long-term trends in distributions. We conclude that Frescalo, which can be seen as a type of occupancy model where an adjustment for overlooked species is made in relation to spatial rather than temporal replication, whilst simultaneously adjusting for variable regional effort, is currently the most sophisticated tool for achieving this. Although recording community-accepted adjustments to data collection practices may allow for a greater application of occupancy modelling or other approaches in the future, methods that seek accurate trends over the long-term are necessarily limited either to scales at which various properties of the data in hand are most likely to be unbiased, or at which the biases are well enough understood to be modelled accurately.

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Schwarzfuchs, Dan, Sagi Shashar, Iftach Sagy, Victor Novack, and Vladimir Zeldetz. "Does the physician in triage strategy improve door-to-balloon time for patients with STEMI?" Emergency Medicine Journal 37, no. 9 (August 4, 2020): 540–45. http://dx.doi.org/10.1136/emermed-2019-209241.

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BackgroundThe physician in triage (PIT) strategy was implemented in the emergency department (ED) of the Soroka University Medical Center (SUMC) to improve overcrowding and waiting time. Our objective in the current study was to assess the impact of the PIT strategy on door-to-balloon time for the treatment of acute ST-elevation myocardial infarction (STEMI).MethodsThe PIT programme began on January 2016, working weekdays between 8:00 and 23:00 hours. We included patients who visited the ED and were diagnosed with STEMI, from November 2014 to February 2018. The primary outcome was improvement in door-to-balloon (D2B) time <90 min between the preintervention and postintervention period. The analysis included a comparison between the two time periods using univariate tests, a time trend analysis illustrated by the locally weighted scatterplot smoothing curves and a regression analysis using generalised estimating equation models. To determine the impact of the PIT, as opposed to other changes in the department, we stratified the population arriving after January 2016 to patients arriving during PIT hours versus patients arriving on weekends and at nights (23:00–8:00 hours).ResultsIn all, 415 patients met all the inclusion criteria of which 237 (57.1%) visited on weekdays 8:00–23:00 hours. The per cent of patients with D2B <90 min was 13.9% higher for postintervention versus preintervention visits (p=0.006). D2B time was significantly shorter by 9 min for postintervention visits (p=0.001). In the postintervention period, patients arriving between 8:00 and 23:00 hours on weekdays were more likely to have D2B <90 min than those arriving nights and weekends; 90/146 (61.6%) vs 47.2% (51/108), respectively, p=0.02. ORs for D2B <90 min was 2.04 (95% CI 1.06 to 3.91) for weekday visits, and 1.90 (0.88 to 4.12) for weekend and night visits.ConclusionThe PIT model in SUMC is associated with D2B reduction for patients with STEMI. To achieve further reduction, both targeted interventions should be performed and PIT strategy should be applied for full time, including nights and weekends.

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Pham, Minh, Penghang Yin, Arjun Rana, Stanley Osher, and Jianwei Miao. "Generalized Proximal Smoothing for Phase Retrieval." Microscopy and Microanalysis 25, S2 (August 2019): 118–19. http://dx.doi.org/10.1017/s1431927619001326.

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Aravkin, Aleksandr, James V. Burke, Lennart Ljung, Aurelie Lozano, and Gianluigi Pillonetto. "Generalized Kalman smoothing: Modeling and algorithms." Automatica 86 (December 2017): 63–86. http://dx.doi.org/10.1016/j.automatica.2017.08.011.

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Wang, Zheng. "An algorithm for generalized monotonic smoothing." Journal of Applied Statistics 27, no. 4 (May 2000): 495–507. http://dx.doi.org/10.1080/02664760050003678.

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Hansbo, Peter. "Generalized Laplacian smoothing of unstructured grids." Communications in Numerical Methods in Engineering 11, no. 5 (May 1995): 455–64. http://dx.doi.org/10.1002/cnm.1640110510.

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Dohrmann, C. R., H. R. Busby, and D. M. Trujillo. "Smoothing Noisy Data Using Dynamic Programming and Generalized Cross-Validation." Journal of Biomechanical Engineering 110, no. 1 (February 1, 1988): 37–41. http://dx.doi.org/10.1115/1.3108403.

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Smoothing and differentiation of noisy data using spline functions requires the selection of an unknown smoothing parameter. The method of generalized cross-validation provides an excellent estimate of the smoothing parameter from the data itself even when the amount of noise associated with the data is unknown. In the present model only a single smoothing parameter must be obtained, but in a more general context the number may be larger. In an earlier work, smoothing of the data was accomplished by solving a minimization problem using the technique of dynamic programming. This paper shows how the computations required by generalized cross-validation can be performed as a simple extension of the dynamic programming formulas. The results of numerical experiments are also included.

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Liu, Wei, Pingping Zhang, Yinjie Lei, Xiaolin Huang, Jie Yang, and Ian Reid. "A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 11620–28. http://dx.doi.org/10.1609/aaai.v34i07.6830.

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Image smoothing is a fundamental procedure in applications of both computer vision and graphics. The required smoothing properties can be different or even contradictive among different tasks. Nevertheless, the inherent smoothing nature of one smoothing operator is usually fixed and thus cannot meet the various requirements of different applications. In this paper, a non-convex non-smooth optimization framework is proposed to achieve diverse smoothing natures where even contradictive smoothing behaviors can be achieved. To this end, we first introduce the truncated Huber penalty function which has seldom been used in image smoothing. A robust framework is then proposed. When combined with the strong flexibility of the truncated Huber penalty function, our framework is capable of a range of applications and can outperform the state-of-the-art approaches in several tasks. In addition, an efficient numerical solution is provided and its convergence is theoretically guaranteed even the optimization framework is non-convex and non-smooth. The effectiveness and superior performance of our approach are validated through comprehensive experimental results in a range of applications.

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Li, Meixia, and Haitao Che. "A Smoothing Inexact Newton Method for Generalized Nonlinear Complementarity Problem." Mathematical Problems in Engineering 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/401835.

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Based on the smoothing function of penalized Fischer-Burmeister NCP-function, we propose a new smoothing inexact Newton algorithm with non-monotone line search for solving the generalized nonlinear complementarity problem. We view the smoothing parameter as an independent variable. Under suitable conditions, we show that any accumulation point of the generated sequence is a solution of the generalized nonlinear complementarity problem. We also establish the local superlinear (quadratic) convergence of the proposed algorithm under the BD-regular assumption. Preliminary numerical experiments indicate the feasibility and efficiency of the proposed algorithm.

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Zhu, Xingwen, and Lixiang Zhang. "A Smoothing Process of Multicolor Relaxation for Solving Partial Differential Equation by Multigrid Method." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/490156.

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This paper is concerned with a novel methodology of smoothing analysis process of multicolor point relaxation by multigrid method for solving elliptically partial differential equations (PDEs). The objective was firstly focused on the two-color relaxation technique on the local Fourier analysis (LFA) and then generalized to the multicolor problem. As a key starting point of the problems under consideration, the mathematical constitutions among Fourier modes with various frequencies were constructed as a base to expand two-color to multicolor smoothing analyses. Two different invariant subspaces based on the 2h-harmonics for the two-color relaxation with two and four Fourier modes were constructed and successfully used in smoothing analysis process of Poisson’s equation for the two-color point Jacobi relaxation. Finally, the two-color smoothing analysis was generalized to the multicolor smoothing analysis problems by multigrid method based on the invariant subspaces constructed.

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Zhang, Cong, Limin Sun, and Ya Xiao. "A Generalized Projetion Gradient Algorithm for Mathematical Programs with Complementary Constraints." Journal of Physics: Conference Series 2289, no. 1 (June 1, 2022): 012019. http://dx.doi.org/10.1088/1742-6596/2289/1/012019.

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Abstract Against the shortcomings that many existing algorithms for solving the standard smoothing nonlinear programming would fail if they were used directly to solve the mathematical programs with complementary constraints( MPCC). By using a complementarity function and the idea of smoothing approximation method, the MPCC problem was transformed into a smoothing nonlinear programming. Combined with the supermemory gradient idea, a generalized projection gradient algorithm is proposed and its global convergence is obtained.

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Mirkin, Leonid, and Ron Zaslavsky. "Sampled-Data H2 Smoothing with Generalized Sampling." IFAC Proceedings Volumes 46, no. 12 (2013): 101–6. http://dx.doi.org/10.3182/20130703-3-fr-4039.00033.

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Pham, Minh, Penghang Yin, Arjun Rana, Stanley Osher, and Jianwei Miao. "Generalized proximal smoothing (GPS) for phase retrieval." Optics Express 27, no. 3 (January 29, 2019): 2792. http://dx.doi.org/10.1364/oe.27.002792.

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Sugimoto, Mitsuru. "Global smoothing properties of generalized Schrödinger equations." Journal d'Analyse Mathématique 76, no. 1 (December 1998): 191–204. http://dx.doi.org/10.1007/bf02786935.

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Miller, David L., and Simon N. Wood. "Finite area smoothing with generalized distance splines." Environmental and Ecological Statistics 21, no. 4 (February 26, 2014): 715–31. http://dx.doi.org/10.1007/s10651-014-0277-4.

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