On the weak convergence and Central Limit Theorem of blurring and nonblurring processes with application to robust location estimation

This article studies the weak convergence and associated Central Limit Theorem for blurring and nonblurring processes. Then, they are applied to the estimation of location parameter. Simulation studies show that the location estimation based on the convergence point of blurring process is more robus...

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Bibliographic Details
Published in:Journal of multivariate analysis 2016-01, Vol.143, p.165-184
Main Authors: Chen, Ting-Li, Fujisawa, Hironori, Huang, Su-Yun, Hwang, Chii-Ruey
Format: Article
Language:English
Subjects:
Blurring process
Central Limit Theorem
Estimating techniques
Parameter estimation
Robust estimation
Simulation
Studies
Theorems
Weak convergence
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Summary:This article studies the weak convergence and associated Central Limit Theorem for blurring and nonblurring processes. Then, they are applied to the estimation of location parameter. Simulation studies show that the location estimation based on the convergence point of blurring process is more robust and often more efficient than that of nonblurring process.
ISSN:0047-259X
1095-7243
DOI:10.1016/j.jmva.2015.09.009