How to simulate a Gaussian process in R with predefined mean and variance

[Mark J.]

Hi everybody

Any ideas how to simulate a Gaussian stationary process in R language using predefined variance and mean?
I have a uni-variate normal distribution for my real life process
Thank you

 

[mathman]

Let X be the uivariate normal. Then Y=σX + m where σ is the standard deviation and m is the mean of the process (Y) that you want to simulate. (I don't know what R language is.)

 

[chiro]

Hey MarkJ.

In R, you should use output = rnorm(n,mean,standard_deviation) to simulate from a normal distribution with n observations given those probabilities (you will get a random vector of size n from this distribution).