# wrapped Normal distribution

**R – Xi'an's Og**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

**O**ne version of the wrapped Normal distribution on (0,1) is expressed as a sum of Normal distributions with means shifted by all relative integers

which, while a parameterised density, has *imho* no particular statistical appeal over the use of other series. It was nonetheless the centre of a series of questions on X validated in the past weeks. Curiously used as the basis of a random walk type move over the unit cube along with a uniform component. Simulating from this distribution is easily done when seeing it as an infinite mixture of truncated Normal distributions, since the weights are easily computed

Hence coding simulations as

wrap<-function(x, mu, sig){ ter = trunc(5*sig + 1) return(sum(dnorm(x + (-ter):ter, mu, sig)))} siw = function(N=1e4,beta=.5,mu,sig){ unz = (runif(N)and checking that the harmonic mean estimator was functioning for this density, predictably since it is lower bounded on (0,1). The prolix originator of the question was also wondering at the mean of the wrapped Normal distribution, which I derived as (predictably)

but could not simplify any further except for x=0,½,1, when it is ½. A simulated evaluation of the mean as a function of μ shows a vaguely sinusoidal pattern, also predictably periodic and unsurprisingly antisymmetric, and apparently independent of the scale parameter σ…

Toleave a commentfor the author, please follow the link and comment on their blog:R – Xi'an's Og.

R-bloggers.com offersdaily e-mail updatesabout R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.