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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Fixed Effects Bayesian Testing in High-Dimensional Linear Mixed Models
高维 线性混合模型 固定效应 贝叶斯检验
2023/5/5
Hypothesis testing on high-dimensional fixed effects is indispensable for investigating the utility of the predictors on response. In this case, the conventional frequentist methods designed for cases...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Group-Orthogonal Subsampling for Big Data Linear Mixed Models
大数据 线性混合模型 群正交 子采样
2023/5/10
Linear mixed model is a popular and common modeling method in statistical analysis. It is computationally difficult to obtain parameter estimates in linear mixed model for big data. The current subsam...
Factors Associated With Serum Albumin in Diabetes Mellitus Type 2 With Microalbuminuria Using Non-Normal Mixed Models: A Prospective Cohort Study
Serum Albumin Diabetes Mellitus Type 2 Risk Factors
2016/1/26
Background: The globally increasing epidemic of diabetes will lead to serious problems including diabetic nephropathy and kidney diseases in near future. The first clinical diagnosable stage in a diab...
HIGH-EFFICIENCY BUILDING SURVEYS BY DYNAMIC AND STATIC DIGITAL IMAGES ORIENTED WITH “MIXED MODELS”
Architecture Digital Surveying Integration Rectification Algorithms Dynamic
2015/5/25
Throughout this paper, a method to efficiently survey buildings by digital images, dynamically and statically acquired, is presented by investigating methodological and analytical aspects and by sugge...
Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies
Efficient Algorithms Multivariate Linear Mixed Models Genome-wide Association Studies
2013/6/17
Multivariate linear mixed models (mvLMMs) have been widely used in many areas of genetics, and have attracted considerable recent interest in genome-wide association studies (GWASs). However, existing...
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Polygenic Modeling Bayesian Sparse Linear Mixed Models
2012/11/23
Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. These two approaches ...
A stochastic variational framework for fitting and diagnosing generalized linear mixed models
Hierarchical model Identify divergent units Large longitudinal data Non-conjugate model Stochastic approximation Variational Bayes
2012/9/17
Variational Bayes computational methods are attracting increasing in-terest because of their ability to scale to large data sets. Here, application of the
non-conjugate variational message passing (N...
spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R
MCMC P-splines spike-and-slab prior normal-inverse-gamma
2011/6/20
The R package spikeSlabGAM implements Bayesian variable selection, model choice,
and regularized estimation in (geo-)additive mixed models for Gaussian, binomial, and
Poisson responses. Its purpose ...
Ridge parameter for g-prior distribution in probit mixed models with collinearity
Ridge parameter for g probit mixed models with collinearity g-prior of Zellner
2011/3/18
In the Bayesian variable selection framework, a common prior distribution for the regression coefficients is the g-prior of Zellner (1986). However, there are two standard cases in which the associate...
Mixed models for longitudinal left-censored repeated measures
Mixed model Repeated measures Left-censoring SAS proc NLMIXED HIV infection
2010/4/29
Longitudinal studies could be complicated by left-censored repeated measures. For example, in Human Immunodeficiency Virus infection, there is a detection limit of the assay used to quantify the plasm...
Bivariate linear mixed models using SAS proc MIXED
Bivariate random effects model Bivariate First Order Auto-regressive process SAS proc MIXED HIV infection
2010/4/29
Bivariate linear mixed models are useful when analyzing longitudinal data of two associated markers. In this paper, we present a bivariate linear mixed model including random effects or first-order au...
Admissible estimators of variance components in normal mixed models
Admissible estimators variance components normal mixed models
2009/9/23
A sulficient condition for an invariant quadratic
estimator of a linear function of the vector of variance components to
be admissible under the mean square &or among all translation
invariant esti...
A Default Conjugate Prior for Variance Components in Generalized Linear Mixed Models(Comment on Article by Browne and Draper)
Choice of prior hierarchical models noninformative priors random effects
2009/9/21
For a scalar random-eect variance, Browne and Draper (2005) have found that the uniform prior works well. It would be valuable to know more about the vector case, in which a second-stage prior on the ...
Testing polynomial covariate effects in linear and generalized linear mixed models
Likelihood Ratio Test Restricted Maximum Likelihood （REML） Score Test
2009/2/11
An important feature of linear mixed models and generalized linear mixed models is that the conditional mean of the response given the random effects, after transformed by a link function, is linearly...
We investigate the problem of wealth distribution from the viewpoint of asset exchange. Robust nature of Pareto’s law across economies, ideologies and nations suggests that this could be an outcome of...