In this document, we introduce five additional examples that motivate our research on testing homogeneity. In particular, we show how to check the assumptions for two linear mixed models to validate the asymptotic distributions of the score test statistics. Then, we give the detailed derivation for the score test statistic. We present the result about the local power of the score test statistic...

© 2013 Mustapha Djeddou et al. 757 This paper deals with the estimation of the time of arrival (TOA) of ultra-wideband signals under IEEE 802.15.4a channel models. The proposed approach is based on a randomness test and consists of determining whether an autoregressive (AR) process modeling an energy frame is random or not by using a distance to measure the randomness. The proposed method uses ...

In the matched-pairs data, McNemar’s test (McNemar, 1947) can be applied only to the case in which there are two possible categories for the outcome. In practice, however, it is possible that the outcomes are classified into multiple categories. Under this situation, the test statistic proposed by Stuart (1955) and Maxwell (1970) is useful, it is actually the generalization of the McNemar’s tes...

For the regression model Yi = m(xi) + σ(xi)2i, i = 1, . . . , m, we propose a new nonparametric diagnostic test for checking the constancy of the conditional variance function σ(x). The proposed test does not assume a known parametric form for the conditional mean function m(x). The test statistic is inspired by recent asymptotic theory in analysis of variance when the number of factor levels i...

The classical tests of homogeneity, such as the twosample Kolmogorov-Smirnov test, do not have a natural extension to comparing two multivariate populations. G. J. Székely and N. K. Bakirov have proposed a new test based on Euclidean distance between sample elements. This test can be applied to testing homogeneity of any two multivariate populations with finite second moments, and the test is r...

This paper is motivated by the comparison of genetic networks based on microarray samples. The aim is to test whether the differences observed between two inferred Gaussian graphical models come from real differences or arise from estimation uncertainties. Adopting a neighborhood approach, we consider a twosample linear regression model with random design and propose a procedure to test whether...

This paper develops and evaluates an approximate procedure for testing homogeneity of an arbitrary subset of correlation coefficients among variables measured on the same set of individuals. The sample may have some missing data. The simple test statistic is a multiple of the variance of Fisher r-to-z transformed correlation coefficients relevant to the null hypothesis being tested and is refer...

Meta-analysis seeks to combine the results of several experiments in order to improve the accuracy of decisions. It is common to use a test for homogeneity to determine if the results of the several experiments are sufficiently similar to warrant their combination into an overall result. Cochran's Q statistic is frequently used for this homogeneity test. It is often assumed that Q follows a chi...

We developed an asymptotically optimal hypothesis test concerning the homogeneity of a Poisson process over various subintervals. Under the null hypothesis, maximum likelihood estimators for the values of the intensity function on the subintervals are determined, and are used in the test for homogeneity.