View : 25 Download: 2

Efficient score estimation and adaptive M-estimators in censored and truncated regression models

Title
Efficient score estimation and adaptive M-estimators in censored and truncated regression models
Authors
Kim C.-K.Lai T.L.
Ewha Authors
김철기
Issue Date
2000
Journal Title
Statistica Sinica
ISSN
1017-0405JCR Link
Citation
vol. 10, no. 3, pp. 731 - 749
Indexed
SCI; SCIE; SCOPUS WOS scopus
Abstract
An adaptive M-estimator of a regression parameter based on censored and truncated data is developed by using B-splines to estimate the efficient score function and a relatively simple cross validation method to determine the number of knots. An iterative algorithm to compute the estimator is also provided. The adaptive estimator is asymptotically efficient, and simulation studies of the finite-sample performance of the adaptive estimator shows that it is superior to other M-estimators for regression analysis of censored and truncated data in the literature. An asymptotic theory of cross validation in the presence of censoring and truncation is also developed in this connection.
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
Files in This Item:
efficient score.pdf(236.21 kB)Download
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE