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  2. Ratio test - Wikipedia

    en.wikipedia.org/wiki/Ratio_test

    In mathematics, the ratio test is a test (or "criterion") for the convergence of a series. where each term is a real or complex number and an is nonzero when n is large. The test was first published by Jean le Rond d'Alembert and is sometimes known as d'Alembert's ratio test or as the Cauchy ratio test.

  3. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    The likelihood-ratio test, also known as Wilks test, [2] is the oldest of the three classical approaches to hypothesis testing, together with the Lagrange multiplier test and the Wald test. [3] In fact, the latter two can be conceptualized as approximations to the likelihood-ratio test, and are asymptotically equivalent.

  4. Convergence tests - Wikipedia

    en.wikipedia.org/wiki/Convergence_tests

    Extensions to the ratio test. The ratio test may be inconclusive when the limit of the ratio is 1. Extensions to the ratio test, however, sometimes allows one to deal with this case. Raabe–Duhamel's test. Let { a n} be a sequence of positive numbers. Define = (+). If

  5. Sequential probability ratio test - Wikipedia

    en.wikipedia.org/wiki/Sequential_probability...

    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. The Neyman-Pearson lemma, by contrast, offers a rule of thumb for ...

  6. Ratio estimator - Wikipedia

    en.wikipedia.org/wiki/Ratio_estimator

    The ratio estimates are asymmetrical and symmetrical tests such as the t test should not be used to generate confidence intervals. The bias is of the order O(1/n) (see big O notation) so as the sample size (n) increases, the bias will asymptotically approach 0. Therefore, the estimator is approximately unbiased for large sample sizes.

  7. Neyman–Pearson lemma - Wikipedia

    en.wikipedia.org/wiki/Neyman–Pearson_lemma

    In statistics, the Neyman–Pearson lemma describes the existence and uniqueness of the likelihood ratio as a uniformly most powerful test in certain contexts. It was introduced by Jerzy Neyman and Egon Pearson in a paper in 1933. [1] The Neyman–Pearson lemma is part of the Neyman–Pearson theory of statistical testing, which introduced ...

  8. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    A system of linear inequalities defines a polytope as a feasible region. The simplex algorithm begins at a starting vertex and moves along the edges of the polytope until it reaches the vertex of the optimal solution. Polyhedron of simplex algorithm in 3D. The simplex algorithm operates on linear programs in the canonical form.

  9. Likelihood ratios in diagnostic testing - Wikipedia

    en.wikipedia.org/wiki/Likelihood_ratios_in...

    Estimation example. Pre-test probability: For example, if about 2 out of every 5 patients with abdominal distension have ascites, then the pretest probability is 40%. Likelihood Ratio: An example "test" is that the physical exam finding of bulging flanks has a positive likelihood ratio of 2.0 for ascites.