"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. ...
Method selection allows you to specify how independent variables are entered into the analysis. Using different methods, you can construct a variety of regression models from the same set of variables. Enter. A procedure for variable selection in which all variables in a block are entered in a...
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...
This chapter considers an example on prostate cancer, and analyzes the weekly sales data of refrigerated 64-ounce orange juice containers from 83 stores in the Chicago area. 展开 关键词: LASSO estimates orange juice penalty‐based variable selection approach prostate cancer regression models ...
The aim is not to compare to other variable selection methods but to show that a simple one can improve or at least keep constant the prediction performances of the PLS models by using only a limited number of variables. 展开 关键词: Variable selection Partial least squares Regression Near ...
The problem of variable selection in neural network regression models with dependent data is considered. In this framework, a test procedure based on the introduction of a measure for the variable relevance to the model is discussed. The main difficulty in using this procedure is related to the ...
VARIABLE SELECTION IN PARTLY LINEAR REGRESSION MODEL WITH DIVERGING DIMENSIONS FOR RIGHT CENSORED DATA. Recent biomedical studies often measure two distinct sets of risk factors: low-dimensional clinical and environmental measurements, and high-dimensional ge... S Ma,P Du - 《Statistica Sinica》 被引...
Variable selection methods in regression: Ignorable problem, outing notable solution Variable selection in regression – identifying the best subset among many variables to include in a model – is arguably the hardest part of model buildin... B Ratner - 《Journal of Targeting Measurement & Analysis...
Methods of variable selection in regression modeling Simulation was used to evaluate the performances of several methods of variable selection in regression modeling: stepwise regression based on partial F-te... Murtaugh,A Paul - Communications in Statistics - Simulation and Computation 被引量: 93发表...
Variable Selection when Confronted with Missing Data Variable selection is a common problem in linear regression.Stepwise methods, such as forward selection, are popular and areeasily available in most statistical packages. The models selectedby these methods have a number of drawbacks: th... ML Zie...