Interval Estimation of the Unknown Exponential Parameter Based on Time Truncated Data
Debasis Kundu,Arnab Koley +1 more
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In this article, the authors considered the statistical inference of the unknown parameter of an exponential distribution based on the time truncated data and provided some inferential results based on unconditional argument.Abstract:
SYNOPTIC ABSTRACTIn this article, we consider the statistical inference of the unknown parameter of an exponential distribution based on the time truncated data. The time truncated data occurs quite often in reliability analysis for type-I or hybrid censoring cases. All results available today are based on the conditional argument that at least one failure occurs during the experiment. In this article, we provide some inferential results based on the unconditional argument. We extend the results for some two-parameter distributions.read more
Citations
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Journal ArticleDOI
Multi-sample progressive Type-I censoring of exponentially distributed lifetimes
TL;DR: In this article, a multi-sample progressive type-I censoring model where k≥2 independent progressively Type-I censored experiments are conducted is introduced. The main objective is the derivation o...
Book ChapterDOI
Inference for exponentially distributed lifetimes
TL;DR: In this article , the results for the case of Type-I hybrid censoring are developed in detail, and the corresponding results for Type-II hybridcensoring are presented, and extensions of these results to the cases of generalized hybrid and unified hybrid CCS cases are detailed.
References
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Journal ArticleDOI
Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution
TL;DR: In this paper, an alternative simple form for the distribution is obtained and is shown to be equivalent to that of Chen and Bhattacharyya (1988), which guarantees at least a fixed number of failures in a life testing experiment.
Journal ArticleDOI
The Sampling Distribution of an Estimate Arising in Life Testing
Abstract: This paper deals with the problem of making inferences about the mean of an exponential distribution when the sample is “time-censored”. The exact sampling distribution of the maximum likelihood estimate is obtained and used to show that the asymptotic sampling theory is inadequate unless the sample size is very large. An approximation to the distribution is proposed for use in small samples and compared with a method suggested by Bartlett (1953a). An alternative estimate is suggested which is both simple and highly efficient in certain circumstances. The methods are illustrated by examples.
Journal ArticleDOI
Hybrid censoring schemes with exponential failure distribution
Rameshwar D. Gupta,Debasis Kundu +1 more
TL;DR: In this article, the authors obtained the exact two-sided confidence interval of θ following the approach of Chen and Bhattacharya (1988), and also obtained the asymptotic confidence intervals in the Hybrid censoring case.
Journal ArticleDOI
Exact confidence bounds for an exponential parameter under hybrid censoring
Shu-Mei Chen,G. K. Bhattacharyya +1 more
TL;DR: In this paper, a mixture of type I and type II censoring schemes, called hybrid censoring, is used to derive the distribution of the maximum likelihood estimator of the mean life.
Book ChapterDOI
Analysis of Progressively Censored Competing Risks Data
TL;DR: This chapter considers competing risk data under progressive type II censoring and focuses on the analysis of the competing risk model when the data are progressively type II censored.