ON AN OPTIMUM PROPERTY OF TWO IMPORTANT STATISTICAL TESTS

By J. B. Simaika. 1941

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing (2015, background): “T H is consistent for MDA whenever P, Q have different means, and further, it is known to be the “uniformly most powerful” test when P, Q are univariate Gaussians under fairly general assumptions [Kariya, 1981, Simaika, 1941, Anderson, 1958, Salaevskii, 1971].”
Alternatives to F-Test in One Way ANOVA in case of heterogeneity of variances (a simulation study) (2010, background): “Hotelling's 2T is a uniform most powerful test for the depicted situation (Simaika, 1941; Anderson, 1958).”
A test for the mean vector with fewer observations than the dimension (2008, background): “[12] J.B. Simaika, On an optimum property of two important statistical tests, Biometrika 32 (1941) 70–80.”
Classification Accuracy as a Proxy for Two Sample Testing (2016, background): “For example, it is known to be the “uniformly most powerful” test when P , Q are univariate Gaussians under fairly general assumptions [15, 16, 17, 18].”
On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives (2014, background): “Our first motivation comes from the fact that there is a big difference between the classical setting of fixing d while letting n→∞, and the high-dimensional (HD) setting obtained when (n, d)→∞ (HD) A test would be called consistent under HD if for any fixed α, the power φ → 1 as (n, d) → ∞…”
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives (2015, background): “See Lehmann & Romano (2006) for a detailed introduction.”
Multivariate Theory for Analyzing High Dimensional Data (2007, background): “It is as expected since Dempster’s test is uniformly most powerful among all tests whose power depends on (µ′µ/γ2), see Simaika (1941).”