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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.
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.
Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1]The choice of the test depends on many properties of the research question.
Sequential analysis was pioneered by Abraham Wald. [24] In 1972, Herman Chernoff wrote an overview of optimal sequential designs, [25] while adaptive designs were surveyed later by S. Zacks. [26] Of course, much work on the optimal design of experiments is related to the theory of optimal decisions, especially the statistical decision theory of ...
Together with the Lagrange multiplier test and the likelihood-ratio test, the Wald test is one of three classical approaches to hypothesis testing. An advantage of the Wald test over the other two is that it only requires the estimation of the unrestricted model, which lowers the computational burden as compared to the likelihood-ratio test.
As far as I understand, this statement in the article is wrong because the W-W test and the K-S-test apply to completely different kinds of statistics. While the W-W test applies to sequences the K-S test is used to analyse the cumulative distribution of some quantity (e.g. mass distribution in a star cluster) where the order does not matter (e ...
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]