In this paper we propose a nonparametric test for conditional heteroskedasticity based on a new measure of nonparametric goodness-of-fit (R2). In analogy with the ANOVA tools for classical linear regression models, the nonparametric R2 is obtained for the local polynomial regression of the residuals from a parametric regression on some covariates. It is close to 0 under the null hypothesis of c...

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 a...

The results of a Monte Carlo study of the size and power of parametric and semiparametric approaches to inference on covariate effects in survival (time-to-events) models in the presence of model misspecification and an independent censoring mechanism are reported. Basic models employed are a parametric model, where both a baseline distribution and the dependence structure of covariates on the ...

Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk because of the multiple testing problem. There is a gap in existing tools, as standard neuroimaging software ca...

The so-called independent component (IC) model states that the observed p-vector X is generated via X = ΛZ + μ, where μ is a pvector, Λ is an invertible matrix, and the centered random vector Z has independent marginals Zi. We consider the problem of testing, on the basis of n i.i.d. copies of X = (X,X), the null hypothesis under which the multivariate marginals X and X are independent. Under a...

multi-environment trials play a significant role in selecting the best cultivars to be used at different locations. the objective of this study was to identify grain and forage yields stability of grass pea advanced lines across different locations. the 14 advanced lines of grass pea, developed by the international center for agricultural research in dry areas (icarda), were tested at three dif...

Advances in technology provide new diagnostic tests for early detection of disease. Frequently, these tests have continuous outcomes. One popular method to summarize the accuracy of such a test is the Receiver Operating Characteristic (ROC) curve. Methods for estimating ROC curves have long been available. To examine covariate effects, Pepe (1997, 2000) and Alonzo and Pepe (2002) proposed distr...

This paper provided an insight to the effective use of inferential statistics for social and behavioural research. As a theoretical paper, it explored the importance of tests of significance emphasizing the need to use the appropriate test for a particular research. It showed that a parametric test is one that involves the estimation of the value of at list one population parameter and the fact...

Normal vectors of a surface are essential in various geometry-related applications. Since a normal vector at a point on a parametric surface is computed by a cross product of two tangent vectors at the point, a regular parametric surface may possess a degenerate normal vector at a point when tangent vectors of the surface are linearly dependent at the point. This paper describes an algorithm wh...

This chapter reviews statistical testing involving phylogenies. We present both the classical framework with the use of sampling distributions involving the bootstrap and permutation tests and the Bayesian approach using posterior distributions. We give some examples of direct tests for deciding whether the data support a given tree or trees that share a particular property, comparative analyse...