Deeply digging the interaction effect in multiple linear regressions using a fractional-power interaction term [PDF]
MethodsX, 2020 In multiple regression Y ~ β0 + β1X1 + β2X2 + β3X1 X2 + ɛ., the interaction term is quantified as the product of X1 and X2. We developed fractional-power interaction regression (FPIR), using βX1M X2N as the interaction term. The rationale of FPIR is that
Xinhai Li +4 more
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Simultaneous Optimization of Nanocrystalline SnO2 Thin Film Deposition Using Multiple Linear Regressions [PDF]
Sensors, 2014 A nanocrystalline SnO2 thin film was synthesized by a chemical bath method. The parameters affecting the energy band gap and surface morphology of the deposited SnO2 thin film were optimized using a semi-empirical method.
Saeideh Ebrahimiasl, Azmi Zakaria
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Multiple Linear Regressions by Maximizing the Likelihood under Assumption of Generalized Gauss-Laplace Distribution of the Error. [PDF]
Comput Math Methods Med, 2016 Multiple linear regression analysis is widely used to link an outcome with predictors for better understanding of the behaviour of the outcome of interest.
Jäntschi L, Bálint D, Bolboacă SD.
europepmc +2 more sources
Comparative Study of Predicting the Molecular Diffusion Coefficient for Polar and Non-polar Binary Gas Using Neural Networks and Multiple Linear Regressions [PDF]
Kemija u Industriji, 2019 In the current study, an artificial neural network (ANN) and multiple linear regressions (MLR) have been used to develop predictive models for the estimation of molecular diffusion coefficients of 1252 polar and non-polar binary gases at multiple ...
Naima Melzi +5 more
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Prediction of Topsoil Texture Through Regression Trees and Multiple Linear Regressions
Revista Brasileira de Ciência do Solo, 2018 : Users of soil survey products are mostly interested in understanding how soil properties vary in space and time. The aim of digital soil mapping (DSM) is to represent the spatial variability of soil properties quantitatively to support decision-making.
Helena Saraiva Koenow Pinheiro +4 more
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Data on estimation for sodium absorption ratio: Using artificial neural network and multiple linear regressions [PDF]
Data in Brief, 2018 In this article the data of the groundwater quality of Aras catchment area were investigated for estimating the sodium absorption ratio (SAR) in the years 2010–2014. The artificial neural network (ANN) is defined as a system of processor elements, called
Majid Radfard +6 more
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The ABC of linear regression analysis: What every author and editor should know [PDF]
European Science Editing, 2021 Regression analysis is a widely used statistical technique to build a model from a set of data on two or more variables. Linear regression is based on linear correlation, and assumes that change in one variable is accompanied by a proportional change in ...
Ksenija Bazdaric +4 more
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Journal of Integrative Agriculture, 2017 Many properties of fruit are influenced by plant nutrition. Fruit firmness is one of the most important fruit characteristics and determines post-harvest life of the fruit.
Ali Mohammadi Torkashvand +2 more
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Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions
IEEE Journal of Translational Engineering in Health and Medicine, 2018 Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates.
Diego Rativa +2 more
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A Comparison of “Neural Networks and Multiple Linear Regressions” Models to Describe the Rejection of Micropollutants by Membranes [PDF]
Kemija u Industriji, 2020 A rejection process of organic compounds by nanofiltration and reverse osmosis membranes was modelled using the artificial neural networks. Three feed-forward neural networks based on quantitative structure-activity relationship (QSAR-NN models ...
Yamina Ammi +2 more
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