Exact Inference for Laplace Quantile, Reliability, and Cumulative Hazard Functions Based on Type-II Censored Data

被引：12

作者：

Zhu, Xiaojun ^{[1
]}

Balakrishnan, Narayanaswamy ^{[1
]}

机构：

[1] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada

来源：

IEEE TRANSACTIONS ON RELIABILITY | 2016年 / 65卷 / 01期

关键词：

Best linear unbiased estimator; statistical bias; confidence interval; exact distribution function; hypoexponential distribution; Kaplan-Meier curve; Laplace distribution; cumulative hazard function; maximum likelihood estimators; mean square error; P-P plot; Q-Q plot; quantile; type-II censoring; variance; DOUBLE EXPONENTIAL-DISTRIBUTION; ORDER-STATISTICS; PARAMETERS; SAMPLES; INTERVALS;

D O I：

10.1109/TR.2015.2451617

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we first present explicit expressions for the maximum likelihood estimates (MLEs) of the location, and scale parameters of the Laplace distribution based on a Type-II right censored sample under different cases. Then, after giving the exact density functions of the MLEs, and the expectations, we derive the exact density of the MLE of the quantile, and utilize it to develop exact confidence intervals for the population quantile. We also briefly discuss the MLEs of reliability and cumulative hazard functions, and how to develop exact confidence intervals for these functions. These results can also be extended to any linear estimators. Finally, we present two examples to illustrate the inferential methods developed here.

引用

页码：164 / 178

页数：15

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