The Mnet Method for Variable Selection
نویسندگان
چکیده
By JIAN HUANG Departments of Statistics & Actuarial Science and Biostatistics, University of Iowa, 221 Schaeffer Hall, Iowa City, Iowa 52242, U.S.A. [email protected] PATRICK BREHENY Departments of Statistics and Biostatistics, University of Kentucky, 817 Patterson Office Tower, Lexington, KY 40506, U.S.A. [email protected] SHUANGGE MA School of Public Health, Yale University, New Haven, Connecticut 06520, U.S.A. [email protected] CUN-HUI ZHANG Department of Statistics, Rutgers University, Piscataway, New Jersey 08854, U.S.A. [email protected]
منابع مشابه
Balancing stability and bias reduction in variable selection with the Mnet estimator
We propose a new penalized approach for variable selection using a combination of minimax concave and ridge penalties. The proposed method is designed to deal with p ≥ n problems with highly correlated predictors. We call the propose approach the Mnet method. Similar to the elastic net of Zou and Hastie (2005), the Mnet also tends to select or drop highly correlated predictors together. However...
متن کاملBayesian inference for high-dimensional linear regression under mnet priors
Abstract: For regression problems that involve many potential predictors, the Bayesian variable selection (BVS) method is a powerful tool, which associates each model with its posterior probabilities, and achieves superb prediction performance through Bayesian model averaging (BMA). Two challenges of using such models are, specifying a suitable prior, and computing posterior quantities for infe...
متن کاملSupplement to “ Bayesian inference for high - dimensional linear regression under the mnet priors ”
Here, a q-dim binary vector γ = (γ1, . . . , γq) ∈ {0, 1}q =: Γ indicates a selected set of predictors, and βγ denotes the subvector of coefficients for the predictors selected by γ. Prior of the BVS model are specified in (3b) – (3d). In this BVS model, (3c) specifies a uniform prior on log σ, a typical choice of non-informative prior for these parameters in linear regression models. And (3d) ...
متن کاملCreating an MHOST Table for MNET An Implementation
This paper discusses details and implementation techniques for an ongoing project called MNET. First, an example socket application is presented and the difficulties of the sockets API is addressed. Then we go into detail as to how MNET is built and how it is added as a linux kernel module with ease. Finally we show other projects that are related to what MNET is trying to fix.
متن کاملA Comparison between New Estimation and variable Selectiion method in Regression models by Using Simulation
In this paper some new methods whitch very recently have been introduced for parameter estimation and variable selection in regression models are reviewd. Furthermore , we simulate several models in order to evaluate the performance of these methods under diffrent situation. At last we compare the performance of these methods with that of the regular traditional variable selection methods such ...
متن کامل