(2010). Variable selection in regression-a tutorial. Journal of Chemometrics, 24(11-12), 728-737.C.M. Andersen, R. Bro, Variable selection in regression--a tutorial, J. Chemom. 24 (2010) 728-737.ANDERSEN, C. M.;
Variable 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 writing the sparse vector...
Variable selectionA challenging problem in the analysis of high-dimensional data is variable selection. In this study, we describe a bootstrap based technique for selecting predictors in partial least-squares regression (PLSR) and principle component regression (PCR) in high-dimensional data. Using a...
Febrero-Bande, M., Gonz´alez-Manteiga, W., & de la Fuente, M. O. (2017). Variable selection in functional additive regression models. In G. Aneiros, E. G. Bongiorno, R. Cao, & P. Vieu (Eds.), Functional Statistics and Related Fields (pp. 113-122). Cham: Springer Interna- ...
Stepwise regressionand other related one-step procedures such asbackward eliminationand forward selection can be easily modified to restrict their search to models that are hierarchically well formulated. The following algorithm provides a more efficient way of generating all possible hierarchically well-for...
Shively TS, Kohn R, Wood S (1999) Variable selection and function estimation in additive nonparametric regression using a data-based prior. J Am Stat Assoc 94:777–794 MATH MathSciNetShively, T., Kohn, R., Wood, S.: Variable selection and function estimation in additive nonparametric ...
Furthermore, some methods able to perform both regression and variable selection simultaneously have recently been proposed. In this tutorial we give a short overview of the main variable selection methods. All Subset Models (ASM) The All Subset Models (ASM) method is the most simple and ...
In deriving a regression model analysts often have to use variable selection, despite of problems introduced by data- dependent model building. Resampling approaches are proposed to handle some of the critical issues. In order to assess and compare several strategies, we will conduct a simulation st...
A. predicted variable B. explanatory variable C. response variable D. independent variable 相关知识点: 试题来源: 解析 C。在回归分析中,因变量也被称为响应变量。A 是预测变量一般指自变量的预测结果,B 解释变量即自变量,D 独立变量错误。反馈 收藏 ...
本文研究了基于面板数据的分位数回归模型的变量选择问题.通过增加改进的自适应Lasso惩罚项,同时实现了固定效应面板数据的分位数回归和变量选择,得到了模型中参数的选择相合性和渐近正态性.随机模拟验证了该方法的有效性.推广了文献[14]的结论.In this paper, we consider the variable selection problem for the quan...