Abstract
A procedure to test fit to a distribution where a minimal sufficient statistic is available, is discussed for testing the Poisson distribution. The test is exact, and is compared with a simpler approximate test. A remarkable correlation between the p-values given by the exact and the approximate procedures is found, and shows the power of the computer over and above what is usually acknowledged.
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References
Lehmann EL, Romano JP (2005) Testing statistical hypotheses, 3rd edn. Springer, New York
Lockhart RA (2011) Conditional limit laws for goodness-of-fit tests. Bernoulli (forthcoming)
Lockhart RA, O’Reilly FJ, Stephens MA (2007) Use of the Gibbs sampler to obtain conditional tests, with applications. Biometrika 94:992–998
Lockhart RA, O’Reilly FJ, Stephens MA (2009) Exact conditional tests and approximate bootstrap tests for the von Mises distribution. J Stat Theory Pract 3:543–554
O’Reilly F, Gracia-Medrano L (2006) On the conditional distribution of goodness-of-fit tests. Commun Stat, Theory Methods 35:541–549
Stephens MA (1986) Tests based on EDF statistics. In: D’Agostino RB, Stephens MA (eds) Chapter 4 in goodness-of-fit techniques. Marcel Dekker, New York
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Stephens, M.A. Goodness-of-Fit and Sufficiency: Exact and Approximate Tests. Methodol Comput Appl Probab 14, 785–791 (2012). https://doi.org/10.1007/s11009-011-9267-2
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DOI: https://doi.org/10.1007/s11009-011-9267-2