IfX1, ...,Xnare random variables we denote byX(1)[less-than-or-equals, slant]X(2)[less-than-or-equals, slant]...[less-than-or-equals, slant]X(n)their respective order statistics. In the case where the random variables are independent and identically distributed, one may demonstrate very strong...

Let N(t) be a non-homogeneous Poisson process with mean value function [Lambda](t) and rate of occurrence [lambda](t). We propose a conditional test of the hypothesis that the process is homogeneous, versus alternatives for which the mean value function is superadditive. Specific models leading...

Several relativistic extensions of the Maxwell–Boltzmann distribution have been proposed, but they do not explain observed lognormal tail-behavior in the flux distribution of various astrophysical sources. Motivated by this question, extensions of classical central limit theorems are developed...

A weighted least squares estimator is used to estimate the hazard functions in Aalen's additive risk model from grouped (and possibly censored) survival data. Counting process techniques are applied to derive a functional central limit theorem for the integrated estimator.