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Sparse Probit Linear Mixed Model [PDF]
Machine Learning, 2017 Linear Mixed Models (LMMs) are important tools in statistical genetics. When used for feature selection, they allow to find a sparse set of genetic traits that best predict a continuous phenotype of interest, while simultaneously correcting for various ...
Cunningham, John P. +5 more
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FedGMMAT: Federated generalized linear mixed model association tests. [PDF]
PLoS Computational BiologyIncreasing genetic and phenotypic data size is critical for understanding the genetic determinants of diseases. Evidently, establishing practical means for collaboration and data sharing among institutions is a fundamental methodological barrier for ...
Wentao Li +3 more
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Model Selection in Linear Mixed Models
Statistical Science, 2013 Linear mixed effects models are highly flexible in handling a broad range of data types and are therefore widely used in applications. A key part in the analysis of data is model selection, which often aims to choose a parsimonious model with other ...
Müller, Samuel +2 more
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Differential Privacy Applications to Bayesian and Linear Mixed Model Estimation [PDF]
The Journal of Privacy and Confidentiality, 2013 We consider a particular maximum likelihood estimator (MLE) and a computationally intensive Bayesian method for differentially private estimation of the linear mixed-effects model (LMM) with normal random errors.
John M. Abowd +2 more
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, 2022 AbstractThe linear mixed model framework is explained in detail in this chapter. We explore three methods of parameter estimation (maximum likelihood, EM algorithm, and REML) and illustrate how genomic-enabled predictions are performed under this framework.
Osval Antonio Montesinos López +2 more
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Bayesian linear mixed model with multiple random effects for prediction analysis on high-dimensional multi-omics data. [PDF]
Bioinformatics, 2023 Hai Y, Ma J, Yang K, Wen Y.
europepmc +3 more sources
Phase II monitoring of auto-correlated linear profiles using multivariate linear mixed model [PDF]
International Journal of Industrial Engineering and Production Research, 2021 In the last few decades, profile monitoring in univariate and multivariate environment has drawn a considerable attention in the area of statistical process control.
Rassoul Noorossana, Somayeh Khalili
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International Journal of Applied Mathematics, Sciences, and Technology for National Defense, 2023 With the crisis in fuel consumption, it is necessary to save fuel consumption by selecting fuel that is quite efficient. The aim of the research is to examine the fuel consumption patterns of vehicles in an area that experiences various weathers so as to
Muhammad Nuraliffudin Saputra +5 more
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Knowledge Discovery and Recommendation With Linear Mixed Model
IEEE Access, 2020 We give a concise tutorial on knowledge discovery with linear mixed model in movie recommendation. The versatility of mixed effects model is well explained.
Zhiyi Chen +3 more
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Statistical inference of a stochastically restricted linear mixed model
AIMS Mathematics, 2023 This article compares a predictor with the best linear unbiased predictor (BLUP) for a unified form of all unknown parameters under a stochastically restricted linear mixed model (SRLMM) in terms of the mean squared error matrix (MSEM) criterion.
Nesrin Güler , Melek Eriş Büyükkaya
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