Inference on p{Y<X} in the weibull case

John I. McCool

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

The probability that a Weibull random variable Y is less than another independent Weibull random variable X is considered for the case where both X and Y have the same, but unknown, shape parameter. Tables, developed by Monte Carlo sampling, are presented whereby 90% confidence limits for this probability may be found in terms of its maximum likelihood estimate for 21 combinations of the size of the sample taken from each of the two populations and the ordered observation number at which the samples are type II censored. A normal approximation is also discussed and its accuracy vis-a-vis the exact values is examined as a function of sample size for a particular case.

Original languageEnglish (US)
Pages (from-to)129-148
Number of pages20
JournalCommunications in Statistics - Simulation and Computation
Volume20
Issue number1
DOIs
StatePublished - Jan 1 1991

Fingerprint

Weibull
Random variables
Random variable
Confidence Limits
Monte Carlo Sampling
Normal Approximation
Shape Parameter
Maximum Likelihood Estimate
Maximum likelihood
Tables
Sample Size
Sampling
Unknown
Observation

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation

Cite this

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Inference on p{Y<X} in the weibull case. / McCool, John I.

In: Communications in Statistics - Simulation and Computation, Vol. 20, No. 1, 01.01.1991, p. 129-148.

Research output: Contribution to journalArticle

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