R help - Dec 2007 - Truncated normal distribution

I am using TNORM - rtnorm to simulate from a truncated normal distribution.
However, the current function available allows us to define the mean and SD
of the non-truncated (original) distribution and then run the simulation.

http://rss.acs.unt.edu/Rdoc/library/msm/html/tnorm.html

I would instead like to define the mean and SD of the non-truncated
distribution. Is there a way I can solve for the original mean and SD (of
non-truncated distribution) from an assume mean and SD for the truncated
distribution?

Thanks !

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I have the following code, where we need to solve for mu and sigma, when we
have mut and sdt. Can you suggest how to use a solve function in R to do
that? I am new to R and am not sure how to go from defining the functions,
to solving for them. 

Thanks


truncated <- function(x)
{

mu=x[1];
sigma=x[2];


f <- function(x) (1/(sigma*sqrt(2*pi)))*exp(-(x-mu)^2/(2*sigma^2));

pdf.fun <- function(x) x*f(x);

sd.fun <- function(x) (x)^2*f(x);

st=integrate(sd.fun,lower=-Inf,upper=1)$value;

a=integrate(pdf.fun,lower=-Inf,upper=1)$value;

a1=integrate(f,lower=-Inf,upper=1)$value;

mut <- a/a1;
sdt <- sqrt((st/a1)-(a/a1)^2);

} 


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