How to generate normal mixture random variables with given covariance function

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How to generate normal mixture random variables with given covariance function

chee
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Re: How to generate normal mixture random variables with given covariance function

Giovanni Petris
On Fri, 2011-04-22 at 09:59 -0400, Chee Chen wrote:
> Dear All,
> Suppose Z_i, i=1,...,m are marginally identically distributed as a two
> normal mixture p0*N(0,1) + (1-p0) *N( miu_i, 1) where miu_i are
> identically distributed according to a mixture and I have  generated
> Z_i one by one .
>
> Now suppose these m random variables are jointly m-dimensional normal

This is not related to R, so you should probably ask the question
somewhere else. The short answer is that the Z_i cannot be jointly
Normally distributed, since they are not marginally Normally
distributed.

Giovanni Petris

>  with correlation matrix M= (m_ij).
> How to proceed next or how to start correctly ?
>
> Question:  
> 1.  Are Z_i, i=1,...,m I have generated jointly normal?
> 2.   How to get them such that they are jointly normal with M
>
> Thank you,
> -Chee
> [[alternative HTML version deleted]]
>
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> and provide commented, minimal, self-contained, reproducible code.

--

Giovanni Petris  <[hidden email]>
Associate Professor
Department of Mathematical Sciences
University of Arkansas - Fayetteville, AR 72701
Ph: (479) 575-6324, 575-8630 (fax)
http://definetti.uark.edu/~gpetris/

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