Standard genetic association tests using case-control data are based on certain assumptions about the population from which study subjects were sampled. Two types of departure from these assumptions have been studied: population stratification and cryptic relatedness. Both types of departure have been called population structure. Each can lead to erroneous inferences due to differences between ...

Impulsive or heavy-tailed processes with innnite variance appear naturally in a variety of practical problems that include wireless communications, teletraac, hidrology, geology and economics. Most signal processing and statistical methods available in the literature have been designed under the assumption that the processes possess nite variance, and they usually breakdown in the presence of i...

We investigate the asymptotic behavior of test statistics outliers for sample drawn from heavy{tailed distributions. We extend classical results of David, Hartley and Pearson (1954) and Grubbs (1969), who considered outlier test statistics for the nite{variance case, to the heavy{tailed in nite variance case. Our main result concerns the limiting distribution of n 1=2On for the outlier statisti...

This paper presents the conditions for robustness to the nonnormality on three test statistics for a general multivariate linear hypothesis, which were proposed under the normal assumption in a generalized multivariate analysis of variance (GMANOVA) model. The proposed conditions require the cumulants of an unknown population’s distribution to vanish in the second terms of the asymptotic expans...

Variances in the American Community Survey are estimated using a replicate weight methodology (Fay, 1995). In counties with small sample sizes, the variance estimates of poverty statistics show wide variation as a function of sample size. Generalized Variance Functions (GVF) can be used to smooth out the uncertainty of the design-based variance estimate. We propose incorporating GVFs with small...