کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
417631 681555 2011 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
FSR methods for second-order regression models
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
FSR methods for second-order regression models
چکیده انگلیسی

Most variable selection techniques focus on first-order linear regression models. Often, interaction and quadratic terms are also of interest, but the number of candidate predictors grows very fast with the number of original predictors, making variable selection more difficult. Forward selection algorithms are thus developed that enforce natural hierarchies in second-order models to control the entry rate of uninformative effects and to equalize the false selection rates from first-order and second-order terms. Method performance is compared through Monte Carlo simulation and illustrated with data from a Cox regression and from a response surface experiment.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 55, Issue 6, 1 June 2011, Pages 2026–2037
نویسندگان
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