Results 1 to 10 of about 1,534,752 (139)
Semiparametric Additive Beta Regression Models
Revstat Statistical Journal, 2021 In this paper, we study a semiparametric additive beta regression model using a parameterization based on the mean and a dispersion parameter. This model is useful for situations where the response variable is continuous and restricted to the unit ...
Germán Ibacache-Pulgar +2 more
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Regression models of Pearson correlation coefficient
Statistical Theory and Related Fields, 2023 We propose two simple regression models of Pearson correlation coefficient of two normal responses or binary responses to assess the effect of covariates of interest. Likelihood-based inference is established to estimate the regression coefficients, upon
Abdisa G. Dufera, Tiantian Liu, Jin Xu
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Remote Sensing, 2022 Tiller are an important biological characteristic of wheat, a primary food crop. Accurate estimation of tiller number can help monitor wheat growth and is important in forecasting wheat yield.
Fei Wu +6 more
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Boosting Functional Regression Models with FDboost
Journal of Statistical Software, 2020 The R add-on package FDboost is a flexible toolbox for the estimation of functional regression models by model-based boosting. It provides the possibility to fit regression models for scalar and functional response with effects of scalar as well as ...
Sarah Brockhaus +2 more
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Spline Semiparametric Regression Models
Journal of Kufa for Mathematics and Computer, 2015 In this paper, we study semiparametric regression models with spline smoothing, and determining the numbers of knots and their locations by using some statistical criteria, a simulation model has been performed.
Ameera Jaber Mohaisen +1 more
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Allergologia et Immunopathologia, 2011 In the health sciences it is quite common to carry out studies designed to determine the influence of one or more variables upon a given response variable. When this response variable is numerical, simple or multiple regression techniques are used, depending on the case.
S, Domínguez-Almendros +2 more
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Revista Colombiana de Estadística, 2017 Regression analysis is a technique widely used in different areas ofhuman knowledge, with distinct distributions for the error term. Itis the case, however, that regression models with bimodal responsesor, equivalently, with the error term following a bimodal distribution are notcommon in the literature, perhaps due to the lack of simple to dealwith ...
MARTÍNEZ-FLÓREZ, GUILLERMO +2 more
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Predicting the Response of Laminated Composite Beams: A Comparison of Machine Learning Algorithms
Frontiers in Built Environment, 2022 A comparative study of machine learning regression algorithms for predicting the deflection of laminated composite beams is presented herein. The problem of the scarcity of experimental data is solved by ample numerically prepared data, which are ...
George C. Tsiatas +2 more
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A Crash Data Analysis through a Comparative Application of Regression and Neural Network Models
Safety, 2023 One way to reduce road crashes is to determine the main influential factors among a long list that are attributable to driver behavior, environmental conditions, vehicle features, road type, and traffic signs. Hence, selecting the best modelling tool for
Lorenzo Mussone +1 more
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Asymmetric Regression Models Bernoulli/LogProportional-Hazard Distribution
Revista Colombiana de Estadística, 2014 In this paper we introduce a kind of asymmetric distribution for non-negative data called log-proportional hazard distribution (LPHF). This new distribution is used to study an asymmetrical regression model for data with limited responses (censored ...
GUILLERMO MARTÍNEZ-FLÓREZ +1 more
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