Hi,
I am trying to figure out how to evaluate the density function of
multivariate normal efficiently for a large data set, the
data set should look like this (take d=2 for example):
data mean
sigma
2.131, 3.000 1.000,1.000
1 0
0 1
1.231,5.141 2.000,2.000
.5 -.1
............. .............
-.1 .4
.........
that is , I need SUM_i (log(dmvnorm(d[i], mu[i], sigma[i])). tried to
rewrite the dmvnorm function from mvtnorm
package, but could not find a satisfactory method to avoid using loops. ( using
those "apply" functions seem to be slower
than loops) . May I get some suggestion on this ? Thanks a lot in advance.
best