Presents a coherent body of theory for the derivation of the sampling distributions of a wide range of test statistics. Emphasis is on the development of practical techniques. A unified treatment of the theory was attempted, e.g., the author sought to relate the derivations for tests on the circle and the two-sample problem to the basic theory for the one-sample problem on the line. The Markovian nature of the sample distribution function is stressed, as it accounts for the elegance of many of the results achieved, as well as the close relation with parts of the theory of stochastic processes. J. KIEFER, K-sample analogues of the Kolmogorov-Smirnov and Cramer-von Mises tests, Ann. Math. Statist. ...  , Correction to A note on the power of a non- parametric test. Ibid. ... 28, Department of Mathematics, University of Washington, 1971. ...  , Random Processes, Oxford University Press, New York, 1962.
|Title||:||Distribution Theory for Tests Based on Sample Distribution Function|
|Publisher||:||SIAM - 1973-01-31|