Advertisement
Published in:
2019 | OriginalPaper | Chapter
1. Multivariate Distributions and Copulas
Author : Claudia Czado
Published in: Analyzing Dependent Data with Vine Copulas
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
Before we describe multivariate distribution, we review some notation and characteristics of univariate distributions. In general, we use capital letters for random variables and small letters for observed values, i.e., we write \(X=x\). Here, we only consider absolutely continuous or discrete distributions, and therefore corresponding (conditional) densities or probability mass functions exist. In both cases, we use the letter f for densities or probability mass functions and the letter F for the corresponding distribution function.