Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...

This repository contains MATLAB scripts and a report for simulating and analyzing Gaussian random variables, focusing on their statistical properties such as mean, variance, and probability density ...

Abstract: A conditional multi-target mean and covariance are calculated based on a Gaussian random field approximation of point processes. We derive a particular solution based on a multi-target model ...

Abstract: Recently, the information bottleneck method, a machine learning framework, was incorporated in several communication engineering related applications. However, most of these applications are ...

SIAM Journal on Applied Mathematics, Vol. 18, No. 4 (Jun., 1970), pp. 721-737 (17 pages) The probability density functions of products of independent beta, gamma and central Gaussian random variables ...

CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...

We prove large and moderate deviation principles for the distribution of an empirical mean conditioned by the value of the sum of discrete i.i.d. random variables. Some applications for combinatoric ...