I have a univariate discrete random variable and a histogram representing its PDF (which is asymmetrical). Is there a known way to increase/decrease the variance of the distribution (i.e. scaling it on the x-axis) while retaining other shape characteristics as much as possible? Preserving the Mean is most important to me.

If there is a way, what would be a good numerical recipe for an efficient implementation?

I went over this Wiki article and also looked on-line, mostly around this approach and its derivatives which aim to minimize deviating from the input histogram in terms of shape.

Thanks