Subset selectionThis article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to be as objective as possible. A probability distribution is first assigned to the ...
Linear regressionSparsityVariable selectionVariational inferenceWe introduce a simple new approach to variable selection in linear regression, and to quantifying uncertainty in selected variables. The approach is based on a new model - the "Sum of Single Effects" (SuSiE) model - which comes from ...
This article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to be as objective as possible. A probability distribution is first assigned to the dependent variabl...
Enter (Regression). A procedure for variable selection in which all variables in a block are entered in a single step. Stepwise. At each step, the independent variable not in the equation that has the smallest probability of F is entered, if that probability is sufficiently small. Variables ...
闲话Variable Selection和Lasso 最近在看变量选择(也叫subset selection),然后来总结一下,想到哪写到哪的随意风格(手动微笑)。[11,12,13]是主要参考的综述文章。 Boosting 和 Stagewise Regression 嗯,我也很惊讶为什么这个Lasso会跟Boosting挂着勾。Lasso这样的带罚项的regression最早的思想来自于linear regression boosti...
闲话Variable Selection和Lasso 最近在看变量选择(也叫subset selection),然后来总结一下,想到哪写到哪的随意风格(手动微笑)。[11,12,13]是主要参考的综述文章。 Boosting 和 Stagewise Regression 嗯,我也很惊讶为什么这个Lasso会跟Boosting挂着勾。Lasso这样的带罚项的regression最早的思想来自于linear regression boosti...
The Bayesian analysis of the variable selection problem in linear regression when using objective priors needs some form of encompassing the class of all submodels of the full linear model as they aredoi:10.1007/0-8176-4487-3_25Giron, F. Javier...
方法选择允许您指定自变量将如何进入到分析中。 通过使用不同的方法,您可以根据相同的变量组构造多个回归模型。 输入(回归)。一种变量选择过程,其中一个块中的所有变量在一个步骤中输入。 逐步。在每一步,不在方程中的具有 F 的概率最小的自变量被选入(如果该概率足够小)。 对于已在回归方程中的变量,如果它们的...
In this work we introduce a new model space prior for Bayesian variable selection in linear regression. This prior is designed based on a recursive constructive procedure that randomly generates models by including variables in a stagewise fashion. We provide a recipe for carrying out Bayesian variab...
Some two-step procedures for variable selection in high-dimensional linear regression. Arxiv preprint arXiv:0810.1644, 2008a.Zhang, J., Jeng, X. J., and Liu, H. (2008), "Some Two-Step Procedures for Variable Selection in High- Dimensional Linear Regression." Preprint available at http://...