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Matrix Variate Logistic Regression Analysis
Asymptotic theory Logistic regression Matrix variate covariates Regularization Tensor object
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2011/6/17
Logistic regression has been widely applied in the field of biostatistics for a long
time. It aims to model the conditional success probability of an event of interest
as the logit function of a lin...
The Loss Rank Criterion for Variable Selection in Linear Regression Analysis
Model selection lasso loss rank principle shrinkage parameter variable se-lection
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2010/11/9
Lasso and other regularization procedures are attractive methods for variable selection, subject to a proper choice of shrinkage parameter. Given a set of potential subsets produced by a regularizatio...
Bayesian Inference for Shape Mixtures of Skewed Distributions, with Application to Regression Analysis
Posterior analysis regression model shape parameter skewness symmetry
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2009/9/22
We introduce a class of shape mixtures of skewed distributions and
study some of its main properties. We discuss a Bayesian interpretation and some
invariance results of the proposed class. We devel...