In this paper we develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specically, our approach first allows for statistical noise, similar to Stochastic frontier analysis, and second, it allows modeling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to...

BACKGROUND Gene, protein, or metabolite expression levels are often non-normally distributed, heavy tailed and contain outliers. Standard statistical approaches may fail as location tests in this situation. OBJECTIVES In three Monte-Carlo simulation studies, we aimed at comparing the type I error levels and empirical power of standard location tests and three adaptive tests [O'Gorman, Can J S...

In this paper we compare two non-stationary time series using non-parametric procedures. Evolutionary spectra are estimated for the two series. Randomization tests are performed on groups of spectral estimates for both related and independent time series. Simulation studies show that in certain cases the tests perform reasonably well. The tests are applied to observed geological and financial t...

With the exception of Bayesian analysis, phylogenetic inference procedures typically identify a best estimate of phylogenetic relationships, a so called point estimate of the phylogeny. However, the point estimate is often relatively uninteresting in itself unless we have some measure of its reliability. This lecture will be about techniques for examining the robustness or significance of the r...