Function-based hypothesis testing in censored two-sample location-scale models
Document Type
Article
Publication Date
1-1-2020
Abstract
Function-based hypothesis testing in two-sample location-scale models has been addressed for uncensored data using the empirical characteristic function. A test of adequacy in censored two-sample location-scale models is lacking, however. A plug-in empirical likelihood approach is used to introduce a test statistic, which, asymptotically, is not distribution free. Hence for practical situations bootstrap is necessary for performing the test. A multiplier bootstrap and a model appropriate resampling procedure are given to approximate critical values from the null asymptotic distribution. Although minimum distance estimators of the location and scale are deployed for the plug-in, any consistent estimators can be used. Numerical studies are carried out that validate the proposed testing method, and real example illustrations are given.
Identifier
85058364458 (Scopus)
Publication Title
Lifetime Data Analysis
External Full Text Location
https://doi.org/10.1007/s10985-018-09456-8
e-ISSN
15729249
ISSN
13807870
PubMed ID
30539363
First Page
183
Last Page
213
Issue
1
Volume
26
Recommended Citation
Subramanian, Sundarraman, "Function-based hypothesis testing in censored two-sample location-scale models" (2020). Faculty Publications. 5560.
https://digitalcommons.njit.edu/fac_pubs/5560
