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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...
Sparse Adaptive Dirichlet-Multinomial-like Processes
sparse coding adaptive parameters Dirichlet-Multinomial Polya urn data-dependent redundancy bound small/large alphabet data compression
2013/6/14
Online estimation and modelling of i.i.d. data for short sequences over large or complex "alphabets" is a ubiquitous (sub)problem in machine learning, information theory, data compression, statistical...
Dirichlet Posterior Sampling with Truncated Multinomial Likelihoods
Dirichlet Posterior Sampling Multinomial Likelihoods
2012/9/18
This document considers the problem of drawing samples from posterior distributions formed under a Dirichlet prior and a truncated multinomial likelihood, by which we mean a Multi-nomial likelihood fu...
Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
Gaussian process multiclass classification multinomial probit approximate inference expectation propagation
2012/9/19
We consider probabilistic multinomial probit classification using Gaussian process (GP) priors. The challenges with the multiclass GP classification are the integration over the non-Gaussian posterior...
Bayesian nonparametric estimation and consistency of mixed multinomial logit choice models
Bayesian consistency blocked Gibbs sampler discrete choice models mixed multinomial logit random probability measures stick-breaking priors
2011/3/24
This paper develops nonparametric estimation for discrete choice models based on the mixed multinomial logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models deriv...
Posterior predictive arguments in favor of the Bayes-Laplace prior as the consensus prior for binomial and multinomial parameters
Bayesian inference binomial distribution invariance noninformative prior
2009/9/24
It is argued that the posterior predictive distribution for the binomial
and multinomial distributions,when viewed via a hypergeometric-like representa-
tion, suggests the uniform prior on the param...
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...
Maxima of the cells of an equiprobable multinomial
multinomial random vectors equiprobable cell independent interest
2009/3/23
Consider a sequence of multinomial random vectors with increasing number of equiprobable cells. We show that if the number of trials increases fast enough, the sequence of maxima of the cells after a ...
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...