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A Regression Test for Exponentiality: Censored and Complete Samples

Carlos W. Brain and Samuel S. Shapiro
Technometrics
Vol. 25, No. 1 (Feb., 1983), pp. 69-76
DOI: 10.2307/1267728
Stable URL: http://www.jstor.org/stable/1267728
Page Count: 8
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A Regression Test for Exponentiality: Censored and Complete Samples
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Abstract

Two new tests for the two-parameter exponential distribution are presented. The test statistics can be used with doubly censored samples, are easy to compute, need no special constants, and have high power compared with several competing tests. The first test statistic is sensitive to monotone hazard functions, and its percentage points can be closely approximated by the standard normal distribution. The second test statistic is sensitive to nonmonotone hazard functions. The chi-squared (2 degrees of freedom) distribution can be used as an approximation to the distribution of this statistic for moderate and large sample sizes. Monte Carlo power estimates and an example are given.

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