Help on probability distribution question
On 11-Oct-2012 17:22:44 Andras Farkas wrote:
Dear All,
I have a questions I would like to ask about and wonder if you
have any thoughts to make it work in R.
1. I work in the field of medicine where physiologic variables
are often simulated, and they can not have negative values.
Most often the assumption is made to simulate this parameters
with a normal distribution but in the "log-domain" to avoid from
negative values to be generated. Since the expected mean and SD
is usually known from the normal domain, using the methods described
in the wikipedia article "Arithmetric moments" I generate ??and ??
and simulate with rlnorm(). At times though the following issue
comes up: I have the mean and SD for the parameters available
from the normal domain, and the covariance matrix from the normal
domain. Then I would like to simulate the values, but to avoid
from negative values being generated I have to fall back on rlnorm
in {compositions}. My issue is though that my covariance matrix is
representing the covariance of the parameters in the normal domain,
as opposed to in the lognormal domain. Any thoughts on how to work
around this?
apreciate the help,
Andras
If I understand your question correctly, if Y is the variable being simulated then you know the mean (M, say) and the variance (V, say) of log(Y). So you can simulate X from a normal distribution with mean M and variance V = S^2 (S = SD of X), and then Y = exp(X): Y <- exp(rnorm(n,M,S)) where n is the number of sampled values you want. When Y is multivariate, with M the vector of means and V the covariance matrix of log(Y), then use a similar approach with the function mvrnorm() from the MASS package: library(MASS) Y <- mvrnorm(n,M,V) Does this help? Ted. ------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at wlandres.net> Date: 11-Oct-2012 Time: 18:51:47 This message was sent by XFMail