Results 1 to 10 of about 12,232,356 (294)
Study of Bayesian variable selection method on mixed linear regression models.
PLoS ONE, 2023 Variable selection has always been an important issue in statistics. When a linear regression model is used to fit data, selecting appropriate explanatory variables that strongly impact the response variables has a significant effect on the model ...
Yong Li, Hefei Liu, Rubing Li
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Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression [PDF]
Journal of Statistical Software, 2014 Inference in quantile analysis has received considerable attention in the recent years. Linear quantile mixed models (Geraci and Bottai 2014) represent a ?exible statistical tool to analyze data from sampling designs such as multilevel, spatial, panel or
Marco Geraci
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Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models [PDF]
2019 IEEE 58th Conference on Decision and Control (CDC), 2019 We consider {\em Mixed Linear Regression (MLR)}, where training data have been generated from a mixture of distinct linear models (or clusters) and we seek to identify the corresponding coefficient vectors. We introduce a {\em Mixed Integer Programming (MIP)} formulation for MLR subject to regularization constraints on the coefficient vectors.
Taiyao Wang, Ioannis Paschalidis
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Body temperature correlates with depressive symptom severity: analysis and extension of prior findings in observational cohorts with more than 19,000 participants [PDF]
Frontiers in PsychiatryObjectivePrior studies have reported that higher body temperature correlates with greater depressive symptoms, but did not adjust for potential confounders.MethodsWe used linear regression models and linear mixed models to assess associations between ...
Severine Soltani +10 more
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Brain Sciences, 2017 Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants.
Tess K. Koerner, Yang Zhang
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Non-linear and mixed regression models in predicting sustainable concrete strength
Construction and Building Materials, 2018 Abstract Most previous research adopting the regression analysis to capture the relationship between concrete properties and mixture-design-related variables was based on the linear approach with limited accuracy. This study applies non-linear and mixed regression analyses to model properties of environmentally friendly concrete based on a ...
Ruoyu Jin, Alfred B O Soboyejo
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The Essentials on Linear Regression, ANOVA, General Linear and Linear Mixed Models for the Chemist [PDF]
, 2020 Michel Thiel +2 more
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On the mixed Kibria–Lukman estimator for the linear regression model
Scientific Reports, 2022 AbstractThis paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria–Lukman estimator by combining the mixed estimator and the Kibria–Lukman estimator.This new estimator is a general estimation, including OLS estimator, mixed estimator and Kibria–Lukman estimator as special cases. In addition, we discuss the
Hongmei Chen, Jibo Wu
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Scientific Reports, 2021 Repeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects regression models were used to perform statistical modeling
Ann L. Oberg +13 more
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Remote Sensing, 2022 Airborne light detection and ranging (lidar) has proven to be a useful data source for estimating forest inventory metrics such as basal area (BA), volume, and aboveground biomass (AGB) and for producing wall-to-wall maps for validation of satellite ...
Schyler Brown +2 more
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