Open AccessBootstrap Based Confidence Interval Estimation of \\[6pt]Quantiles for Current Status Data
Author(s) -
Wei Chen,
Fengling Ren
Publication year - 2021
Publication title -
international journal of statistics and probability
Language(s) - English
Resource type - Journals
eISSN - 1927-7040
pISSN - 1927-7032
DOI - 10.5539/ijsp.v10n5p38
Subject(s) - quantile , confidence interval , mathematics , statistics , nuisance parameter , interval (graph theory) , interval estimation , data set , current (fluid) , simple (philosophy) , econometrics , estimator , philosophy , epistemology , combinatorics , electrical engineering , engineering
In this paper, we proposed a bootstrap approach to construct the confidence interval of quantiles for current status data, which is computationally simple and efficient without estimating nuisance parameters. The reasonability of the proposed method is verified by the well performance presented in the extensive simulation study. We also analyzed a real data set as illustration.