2005. Variable selection in neural network regression models with dependent data: a subsampling approach. Computational Statistics & Data Analysis. 48, p.415 - 429.M. La Rocca and C. Perna, Variable selection in neural network regression models with dependent data: a subsampling approach. ...
"Variable selection methods in regression: Ignorable problem, outing notable solution". Journal of Targeting, Measurement and Analysis for Marketing 18.1, pp. 65-75. doi: 10.1057/jt.2009.26.B. Ratner, Variable selection methods in regression: ignorable problem, outing notable solution, J. Target. ...
Forward selection Main idea: add one variable at each time. Steps: Start with no covariate in the model Add the most significant covariate: ①Fit p simple linear regression models y=β0+β1xj+ϵ , for j=1,...,p . For each model, calculate the p -value using single t -test for...
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- ...
a polynomial regression model that excludes hierarchically inferior predictors (i.e., lower-order terms) is considered to be not well formulated. Existing variable-selection algorithms do not take into account the hierarchy of predictors and often select as "best" a model that is not hierarchically...
14 Variable Selection for Regression Analysis 14.1 Regression Analysis In the preceding chapter, we described the application of branch-and-bound methods for the selection of variables for cluster analysis and pat-tern recognition. There are, however, other important variable selection applications 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...
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 ...
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 ...
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...