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The Wald–Wolfowitz runs test (or simply runs test), named after statisticians Abraham Wald and Jacob Wolfowitz is a non-parametric statistical test that checks a randomness hypothesis for a two-valued data sequence. More precisely, it can be used to test the hypothesis that the elements of the sequence are mutually independent.
The Wald–Wolfowitz runs test tests for the number of bit transitions between 0 bits, and 1 bits, comparing the observed frequencies with expected frequency of a random bit sequence. Information entropy; Autocorrelation test; Kolmogorov–Smirnov test; Statistically distance based randomness test.
There are several reasons to prefer the likelihood ratio test or the Lagrange multiplier to the Wald test: [18] [19] [20] Non-invariance: As argued above, the Wald test is not invariant under reparametrization, while the likelihood ratio tests will give exactly the same answer whether we work with R, log R or any other monotonic transformation ...
The sequential probability ratio test (SPRT) is a specific sequential hypothesis test, developed by Abraham Wald [1] and later proven to be optimal by Wald and Jacob Wolfowitz. [2] Neyman and Pearson's 1933 result inspired Wald to reformulate it as a sequential analysis problem.
Abraham Wald (/ w ɔː l d /; Hungarian: Wald Ábrahám, Yiddish: אברהם וואַלד; () 31 October 1902 – () 13 December 1950) was a Jewish Hungarian mathematician who contributed to decision theory, [1] geometry and econometrics, and founded the field of sequential analysis. [2]
Jacob Wolfowitz (March 19, 1910 – July 16, 1981) was a Polish-born American Jewish statistician and Shannon Award-winning information theorist. He was the father of former United States Deputy Secretary of Defense and World Bank Group President Paul Wolfowitz .
A randomness test (or test for randomness), in data evaluation, is a test used to analyze the distribution of a set of data to see whether it can be described as random (patternless). In stochastic modeling , as in some computer simulations , the hoped-for randomness of potential input data can be verified, by a formal test for randomness, to ...
The one-sample Wilcoxon signed-rank test can be used to test whether data comes from a symmetric population with a specified center (which corresponds to median, mean and pseudomedian). [11] If the population center is known, then it can be used to test whether data is symmetric about its center. [12]