Restricted one way analysis of variance using the empirical likelihood ratio test

Restricted one way analysis of variance using the empirical likelihood ratio test

Empirical likelihood (EL) ratio tests are developed for testing for or against the hypothesis that k-population means μ1, μ2, . . . , μk are isotonic with respect to some quasi-order ≼ on {1, 2, . . . , k}. The null asymptotic distributions are derived and are shown to be of chibar squared type. The asymptotic power of the proposed test for testing for equality of these means against the order ...

The Two - Way Likelihood Ratio ( G ) Test

These integrations can sometimes be performed analytically, or using some numerical integration techniques. However, we will focus instead on a simple heuristic method which is related to the χ statistics discussed above. Note that David MacKay [3] explicitly assumes the parameters have an ’intrinsic’ arity to them (multinomials with an intrinsic number of bins). This assumption may not be alwa...

An Empirical Likelihood Ratio Test for Normality

The empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this paper. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using the Monte Carlo simulation technique. The power comparisons against a wide range of alternative distributions show that the ELR test is the most powerful of these tests in certain s...

The One-way Analysis of Variance

Teaching Principles of One-Way Analysis of Variance Using

I present an active learning classroom exercise illustrating essential principles of one-way analysis of variance (ANOVA) methods. The exercise is easily conducted by the instructor and is instructive (as well as enjoyable) for the students. This is conducive for demonstrating many theoretical and practical issues related to ANOVA and lends itself to multiple possible configurations of ANOVA re...