I'm trying to get some intuition for multivariate analysis. Thought it would be good to visualise, say, the .95 probability contour for a multivariate normal.
I'm looking for suggestions on an efficient way to do this in R.
My attempt was to generate a bunch of vectors $\boldsymbol v=(cos(x), sin(x))'$ for evenly spaced x in $[0,2\pi]$ and then try to manipulate the cdf to find what constant $k$ made $F(k*\boldsymbol v)=.95$ (when $\boldsymbol \mu = \boldsymbol0$ and $\boldsymbol \Sigma$ arbitrary).
Couldn't get this working and wondered if there was a better approach. I didn't have much luck with the R package I tried - mvtnorm - not sure what they mean by 'equicoordinate' quantile?