PDF4PRO ⚡AMP

Modern search engine that looking for books and documents around the web

Example: marketing

Chapter 3 Random Vectors and Multivariate Normal …

Chapter 3 Random Vectors and MultivariateNormal Random vectorsDefinition Random Vectors are Vectors of random83 BIOS 2083 Linear ModelsAbdus S. Wahedvariables. For instance,X= ,where each element represent a Random variable, is a Random Mean and covariance matrix of a Random mean (expectation) and covariance matrix of a Random vectorXis de-fined as follows:E[X]= E[X1]E[X2]..E[Xn] ,andcov(X)=E {X E(X)}{X E(X)}T = 21 1n 21 n1 2n ,( )where 2j=var(Xj)and jk=cov(Xj,Xk)forj, k=1,2.

Σ = AAT (Cholesky decomposition). Then, by definition of multivariate normal distribution, X= AZ+μ, where Z is a random sample from a N(0,1) distribution. Now, Chapter 3 95. BIOS 2083 Linear Models Abdus S. Wahed 0 5 10 15 20 0 0.02 0.04 …

Tags:

  Normal, Vector, Multivariate, Decomposition, Cholesky, Vectors and multivariate normal, Cholesky decomposition

Information

Domain:

Source:

Link to this page:

Please notify us if you found a problem with this document:

Spam in document Broken preview Other abuse

Transcription of Chapter 3 Random Vectors and Multivariate Normal …

Related search queries