The main property of a discrete joint probability distribution can be stated as the sum of all non-zero probabilities is 1. The next line shows this as a formula. The marginal distribution of X can be ...
1 Department of Economics, Georgia State University, Atlanta, GA, USA. 2 Department of Economics, Simon Fraser University, Burnaby, Canada. 3 Department of Mathematics and Statistics, York University, ...
The range of correlation coefficient of any bivariate discrete random vector with finite or countably infinite values is derived. We show analytically that the normal-transformed discrete bivariate ...
Variable selection is needed and performed in almost every field and a large literature on it has been established, especially under the context of linear models or for complete data. Many authors ...
Abstract: The distribution of has been studied by several authors especially when and are independent random variables and come from the same family. However, there is relatively little work of this ...
This repository contains recitation class materials for UM-SJTU Joint Institute course VE401/ECE4010J, Probabilistic Methods in Engineering, taught by Dr. Horst Hohberger. It aims to visualize and ...
ABSTRACT: We start with analyzing stochastic dependence in a classic bivariate normal density framework. We focus on the way the conditional density of one of the random variables depends on ...
A random variable is a mapping from every element in the sample space, i.e., every realization or outcome, to a real number. Technically, a random variable is measurable mapping, i.e., {w : X(w) <= x} ...
In this paper, we propose a new transformation of circular random variables based on circular distribution functions, which we shall call inverse distribution function (idf) transformation. We show ...
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