Non-rigid registration of MR images to a common reference image results in deformation fields, from which anatomical differences can be statistically assessed, within and between populations. Without further assumptions, nonparametric tests are required and currently the analysis of deformation fields is performed by permutation tests. For deformation fields, often the vector magnitude is chose...

We first note that tests for interaction are missing in virtually all textbooks on nonparametric statistics. We will discuss some reasons why this is so. We then make a case for featuring tests for interaction in the course. By learning how to use median polish and graphical displays students can begin to conceptualize what an interaction means. This will strengthen their understanding of addit...

In environmental and agricultural studies, it is often of interest to compare spatial variables across different regions. Traditional statistical tools that assume independent samples are inadequate, because of potential spatial correlations. In this paper, such spatial dependence is accounted for by a random field model, and a non-parametric test is developed to compare the overall distributio...

This paper considers the problem of comparing two processes with panel data. A nonparametric test is proposed for detecting a monotone change in the link between the two process distributions. The test statistic is of CUSUM type, based on the empirical distribution functions. The asymptotic distribution of the proposed statistic is derived and its finite sample property is examined by bootstrap...

Computational chemistry is a largely empirical field that makes predictions with substantial uncertainty. And yet the use of standard statistical methods to quantify this uncertainty is often absent from published reports. This article covers the basics of confidence interval estimation for molecular modeling using classical statistics. Alternate approaches such as non-parametric statistics and...

Liu, Cheng Ph.D., Purdue University, December 2013. Non-parametric Spatial Models. Major Professor: Hao Zhang. Covariance functions play a central role in spatial statistics. Parametric covariance functions have been used in most of the existing works on the analysis of spatial data. The primary reason for this is that the classes of parametric covariance functions guarantee that the fitted cov...

This paper discusses a class of tests of lack-of-fit of a parametric regression model when design is non-random and uniform on [0,1]. These tests are based on certain minimized distances between a nonparametric regression function estimator and the parametric model being fitted. We investigate asymptotic null distributions of the proposed tests, their consistency and asymptotic power against a ...

OBJECTIVE To compare the ability of a rank-invariant non-parametric method with that of kappa statistics to evaluate the reliability of the Swedish version of the Tampa Scale for Kinesiophobia and the Self-Efficacy Scale by identifying systematic and random disagreement. The aim was, further, to compare 2 different statistical approaches to obtain a global value from multi-item scales. DESIGN...