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A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression
Blockwise Descent Algorithm Group-penalized Multiresponse Multinomial Regression
2015/8/21
In this paper we purpose a blockwise descent algorithm for grouppenalized multiresponse regression. Using a quasi-newton framework we extend this to group-penalized multinomial regression. We give a p...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Bayesian auxiliary variable models for binary and multinomial regression
Auxiliary variables Bayesianb inary and multinomial regression Model averaging Scale mixture of normals
2009/9/21
In this paper we discuss auxiliary variable approaches to Bayesia
binary and multinomial regression. These approaches are ideally suited to au
tomated Markov chain Monte Carlo simulation. In the rst...
Bayesian multinomial regression with class-specific predictor selection
Bayesian model averaging classification Markov chain MonteCarlo multinomial models
2010/3/17
Consider a multinomial regression model where the response,
which indicates a unit’s membership in one of several possible unordered
classes, is associated with a set of predictor variables. Such
m...
