> I presume that you want the density of a multivar normal distrib. You
> don't calculate the inverse; you just need the quadratic form. I think
> that Searle's matrix algebra book gives the computations. off hand, for
> the quad form x'A-1x I'd get the cholesky factor of A = LL' and solve
>
Alan Miller schrieb:
> Mention of the covariance matrix suggests that it is
> the multivariate normal which is wanted, not the simple
> univariate normal.
Of course the multivariate normal.
> The multivariate normal integral is much more difficult.
To be concrete i have to calculate the dens
Gökhan wrote in message <[EMAIL PROTECTED]>...
>
>Hi!
>I wonder how the public is evaluating the normal distribution function
>in realworld applications. I am implementing some methods where i have
>to calculate different times probability functions relying on normal
>distribution functions with
G?khan <[EMAIL PROTECTED]> wrote:
: Hi!
: I wonder how the public is evaluating the normal distribution function
I presume that you want the density of a multivar normal distrib. You
don't calculate the inverse; you just need the quadratic form. I think
that Searle's matrix algebra book gives
Hi!
I wonder how the public is evaluating the normal distribution function
in realworld applications. I am implementing some methods where i have
to calculate different times probability functions relying on normal
distribution functions with steadily changing covariance matrix and mean
values.
