[R] generate bi-variate normal data
markleeds at verizon.net
markleeds at verizon.net
Sat Jul 1 07:27:09 CEST 2006
>From: "Shin, David" <david.shin at pearson.com>
>Date: Sat Jul 01 00:15:21 CDT 2006
>To: "'r-help at stat.math.ethz.ch'" <r-help at stat.math.ethz.ch>
>Subject: [R] generate bi-variate normal data
it's an interesting question. someone else
on this list can answer more explicitly but
i think you have to use the result for the multivariate
normal distribution ( bivariate case ) where , if the
joint is normal , then the conditional is normal also
with parameters a function of the 2 means and the elements of
the covariance matrix. the result in any decent mathematical statistics such as casella berger. so, given the one column, generate the other column conditionally using the formula and then the joint dist will be bivariate normal.
>Dear all,
>
>I would like to generate bi-variate normal data given that the first column
>of the data is known. for example:
>I first generate a set of data using the command,
>x <- rmvnorm(10, c(0, 0), matrix(c(1, 0, 0, 1), 2))
>
>then I would like to sum up the two columns of x:
>x.sum <- apply(x, 1, sum)
>
>now with x.sum I would like to generate another column of data, say y, that
>makes cbind(x.sum, y) follow a bi-variate normal distribution with mean =
>c(0, 0) and sigma = matrix(c(1, 0, 0, 1),2)
>
>I will appreciate for all insights.
>
>David s.
>
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