Truncated Normal Distribution

September 3, 2009

(This article was first published on Quantitative Ecology, and kindly contributed to R-bloggers)

Many distributions may be used to describe patterns that are non-negative; however, there are not as many choices when an upper bound is also needed (although the beta distribution is very flexible). For various reasons, truncated distributions are sometimes preferred, and the truncated normal is particularly popular. While R has a package that includes the standard functions for this distribution (see rtnorm, dtnorm, etc. in the msm pacakge), the true expectation and variance of the distribution may be of interest. It turns out that the first two moments of the truncated normal are not too hard to calculate (but worth writing functions for):

##return the expectation of a truncated normal distribution

##return the variance of a truncated normal distribution

> library(msm)
> a=rtnorm(1000000,-5,2,1,3)
> paste(mean(a),var(a))
[1] "1.52135857341077 0.197281057170982"
> paste(mean.tnorm(-5,2,1,3),var.tnorm(-5,2,1,3))
[1] "1.52090857118 0.197111175109889"

To leave a comment for the author, please follow the link and comment on their blog: Quantitative Ecology. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)