کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
1147832 957801 2013 20 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
Adaptive estimation of the conditional cumulative distribution function from current status data
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موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
Adaptive estimation of the conditional cumulative distribution function from current status data
چکیده انگلیسی


• We propose an adaptive estimator for conditional cumulative distribution function from current status data.
• The estimator is built by minimization of a least-square contrast followed by a model selection procedure.
• Minimax rates over anisotropic balls are computed.
• A numerical study emphasizes the impact of the distance between the observation and survival time distribution.

Consider a positive random variable of interest Y depending on a covariate X, and a random observation time T independent of Y given X. Assume that the only knowledge available about Y is its current status at time T  : δ=I{Y≤T}δ=I{Y≤T} with II the indicator function. This paper presents a procedure to estimate the conditional cumulative distribution function F of Y given X   from an independent identically distributed sample of (X,T,δ)(X,T,δ).A collection of finite-dimensional linear subsets of L2(R2)L2(R2) called models are built as tensor products of classical approximation spaces of L2(R)L2(R). Then a collection of estimators of F is constructed by minimization of a regression-type contrast on each model and a data driven procedure allows to choose an estimator among the collection. We show that the selected estimator converges as fast as the best estimator in the collection up to a multiplicative constant and is minimax over anisotropic Besov balls. Finally simulation results illustrate the performance of the estimation and underline parameters that impact the estimation accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 143, Issue 9, September 2013, Pages 1466–1485
نویسندگان
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