کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
417648 681560 2011 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A fast procedure for calculating importance weights in bootstrap sampling
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
A fast procedure for calculating importance weights in bootstrap sampling
چکیده انگلیسی

Importance sampling is an efficient strategy for reducing the variance of certain bootstrap estimates. It has found wide applications in bootstrap quantile estimation, proportional hazards regression, bootstrap confidence interval estimation, and other problems. Although estimation of the optimal sampling weights is a special case of convex programming, generic optimization methods are frustratingly slow on problems with large numbers of observations. For instance, interior point and adaptive barrier methods must cope with forming, storing, and inverting the Hessian of the objective function. In this paper, we present an efficient procedure for calculating the optimal importance weights and compare its performance to standard optimization methods on a representative data set. The procedure combines several potent ideas for large-scale optimization.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 55, Issue 1, 1 January 2011, Pages 26–33
نویسندگان
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