SECTION 15.18 WALD-WOLFOWITZ TEST

The Wald-Wolfowitz test uses a run test to test the hypothesis
that two sample distributions are from the same underlying theoretical
distributions. See S. Siegel and N. J. Castellan, *Nonparametric
Statistics*, 2nd ed., 1988, pp. 58-64.

Be sure to CALL DFLT before calling WALDWOLF and to include the COMMON/BPRINT/ common block. The call is

CALL WALDWOLF(A1,A2,N1,N2,IRUN,IS,IL,ZVAL) where A1 = DOUBLE PRECISION array dimensioned A1(N1) containing the first sample (input) A2 = DOUBLE PRECISION array dimensioned A2(N2) containing the second sample (input) N1,N2 = sample sizes (input) IRUN = the number of runs (output) IS = LOGICAL variable set to .TRUE. if small sample test is feasible and gives significant difference (output) IL = LOGICAL variable set to .TRUE. if asymptotic test is performed (output), in which case ZVAL = DOUBLE PRECISION scalar containing the z-value (output)

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