On 28/07/12 05:45, Anders Holm wrote:
Dear list members
I need a function that calculates the bivariate normal distribution for each observation.
It is part of a likelihood function and I have 1000's of cases. As I understand it I
cannot use packages like "mvtnorm" because it requres a covariance matrix of
the same dimension as the number of observations.
Huh? Where ever did you get that idea? (Makes no sense at all,
as far as I can see.)
Basically what I need is a function that takes as arguments a n*2 matrix of
bivariate values given a common mean and covariance matrix, where n is the
number of cases and which returns a n*1 vector of the probabilities of the
bivariate normal distribution of the n*2 vector of values.
Sorry, I must be a bit dim, but I don't follow this at all.
Anyhow, either dmnorm() from the "mnormt" package or
dmvnorm() from the "mvtnorm" package should, properly applied,
do everything that you want.
cheers,
Rolf
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