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On BIC's Selection Consistency for Discriminant Analysis
BIC Discriminant Analysis Selection Consistency
2016/1/19
Linear and quadratic discriminant analysis are two very useful classification methods, for which the problem of variable selection is of fundamental impor-tance. To this end, a BIC-type selection crit...
Consistency of Multidimensional Convex Regression
nonparametric regression multidimensional convex functions asymptotic properties consistency
2015/7/6
Convex regression is concerned with computing the best fit of a convex function to a data set of n observations in which the independent variable is (possibly) multidimensional. Such regression ...
On model selection consistency of M-estimators with geometrically decomposable penalties
model selection consistency M-estimators geometrically decomposable penalties
2013/6/14
Penalized M-estimators are used in many areas of science and engineering to fit models with some low-dimensional structure in high-dimensional settings. In many problems arising in bioinformatics, sig...
On the Convergence and Consistency of the Blurring Mean-Shift Process
Mean-shift Convergence Consistency Clustering,γ-divergence Super robustness
2013/6/13
The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the "blurring" mean shi...
The Lasso is a popular statistical tool invented by Robert Tibshirani for linear regression when the number of covariates is greater than or comparable to the number of observations. The validity of t...
The subset argument and consistency of MLE in GLMM: Answer to an open problem and beyond
Cramer consistency crossed random effects MLE GLMM,salamander mating data subset argument Wald consistency
2013/4/27
We give answer to an open problem regarding consistency of the maximum likelihood estimators (MLEs) in generalized linear mixed models (GLMMs) involving crossed random effects. The solution to the ope...
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Classification Asymmetric Label Noise Consistency Maximal Denoising
2013/4/27
In many real-world classification problems, the labels of training examples are randomly corrupted. Previous theoretical work on classification with label noise assumes that the two classes are separa...
Consistency of M estimates for separable nonlinear regression models
Nonlinear regression separable models con-sistency robust estimation.
2012/9/18
Consider a nonlinear regression model :yi =g(xi, 兤) +ei, i = 1, ..., n,where thexi are random predictorsxi and兤is the unknown parameter vector ranging in a set set 儲伡Rp. All known results on the consi...
On the consistency of AUC Optimization
AUC consistency surrogate loss cost-sensitive learning learning to rank
2012/9/18
AUC (area under ROC curve) is an important evaluation criterion, which has been popularly used in diverse learning tasks such as class-imbalance learning, cost-sensitive learning, learning to rank and...
Tight conditions for consistency of variable selection in the context of high dimensionality
variable selection nonparametric regression set estimation sparsity pattern
2011/7/6
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of variables is very large. The main focus is on the situation where the numb...
Posterior Consistency of Nonparametric Conditional Moment Restricted Models
identified region limited information likelihood sieve approximation nonparametric instrumental variable ill-posed problem partial identification Bayesian inference
2011/6/20
This paper addresses the estimation of the nonparametric conditional moment
restricted model that involves an infinite dimensional parameter g0. We
estimate it in a quasi-Bayesian way based on the l...
Consistency of maximum-likelihood and variational estimators in the Stochastic Block Model
maximum-likelihood Stochastic Block Model
2011/6/17
The stochastic block model (SBM) is a probabilistic model de-
signed to describe heterogeneous directed and undirected graphs. In this
paper, we address the asymptotic inference on SBM by use of max...
Consistency of Markov chain quasi-Monte Carlo on continuous state spaces
Completely uniformly distributed coupling iterated function mappings Markov chain Monte Carlo
2011/6/17
The random numbers drivingMarkov chainMonte Carlo (MCMC)
simulation are usually modeled as independent U(0, 1) random variables.
Tribble [Markov chain Monte Carlo algorithms using completely
unifor...
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...
Consistency of Bayesian Linear Model Selection With a Growing Number of Parameters
Bayesian model selection growing number of parameters Posterior model consistency consistency of Bayes factor consistency of posterior odds ratio Gibbs sampling
2011/3/18
Linear models with a growing number of parameters have been widely used in modern statistics. One important problem about this kind of model is the variable selection issue. Bayesian approaches, which...