In the common nonparametric regression model the problem of testing for a specific parametric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process of pseudo residuals. The process converges weakly to a Gaussian process with a complicated covariance kernel depending on the data generating process. In the ...

We introduce a nonparametric test intended for large-scale simultaneous inference in situations where the utility of distribution-free tests is limited because of their discrete nature. Such situations are frequently dealt with in microarray analysis where the number of tests is much larger than the sample size. The proposed test statistic is based on a certain distance between the distribution...

For real-valued x1, x2 , ..., xn with real-valued “responses” y1, y2 , ...,yn and “scores” s1, s2, ..., sn we solve the problem of computing the maximum of C(k) = Σh=1,...,n sh I[yh ≥ k(xh)] over all convex functions k on R1. The article describes a recursive relation and an algorithm based on it to compute this value and an optimal k in O(n3) steps. For a special choice of scores, max C(k) can...

8 The XL-mHG test is a semiparametric test for enrichment in ranked lists with boolean (0/1-valued) entries. It is a generalization of the nonparametric mHG test, designed to provide some control over the kind of enrichment that is being tested for, and to allow a flexible trade-off between the sensitivity and robustness of the test. Here, I describe an improved algorithm to efficiently calcula...

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...

Identification in censored regression analysis and hazard models of duration outcomes relies on the condition that censoring points are independent of latent outcomes, an assumption which may be questionable in many settings. This note proposes a test for this assumption based on a Kolmogorov-Smirnov-like test statistic comparing two different nonparametric estimators for the latent outcome cdf...

The use of the Kolmogorov-Smirnov (KS) statistic for testing hypotheses regarding activation in blood oxygenation level-dependent functional MRI data is critiqued on both theoretical and empirical grounds. Theoretically, it is argued that the KS test is formally unable to support inferences of interest to most neuro-imaging studies and has reduced sensitivity compared with parametric alternativ...

We study the drift of stationary diffusion processes in a time series analysis of the autoregression function. A marked empirical process measures the difference between the nonparametric regression functions of two time series. We bootstrap the distribution of a Kolmogorov-Smirnov-type test statistic for two hypotheses: Equality of regression functions and shifted regression functions. Neither...