Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/103349
Title: Goodness-of-fit tests based on P-P probability plots
Authors: Gan, F.F. 
Koehler, K.J.
Issue Date: Aug-1990
Source: Gan, F.F.,Koehler, K.J. (1990-08). Goodness-of-fit tests based on P-P probability plots. Technometrics 32 (3) : 289-303. ScholarBank@NUS Repository.
Abstract: Two goodness-of-fit statistics, based on measures of linearity for standardized P-P plots, are proposed and simple approximations for percentage points of these statistics are presented for testing the fit of exponential, Gumbel (Weibull), and normal (lognormal) probability models with unknown parameters. Results of extensive Monte Carlo power comparisons with other goodness-of-fit tests are summarized. The proposed tests are shown to have superior power for detecting light-tailed and moderate-tailed alternatives to the exponential distribution, but statistics based on measures of linearity for Q-Q plots tend to be more powerful against relatively heavy-tailed alternatives to hypothesized distributions with more moderate tails, such as the normal and Gumbel distributions.
Source Title: Technometrics
URI: http://scholarbank.nus.edu.sg/handle/10635/103349
ISSN: 00401706
Appears in Collections:Staff Publications

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