On 3/28/06, Prof Brian Ripley [EMAIL PROTECTED] wrote:
You need to learn to supply adequate information. The current
version of sn *does* have such an argument, and I was careful to check.
So it seems that you are using an unstated obselete version of sn.
Do ugrade as the posting guide asked
Dear All,
I am working with skewed-t copula in my research recently, so I needed to
write an mle
procedure instead of using a standard fit one; I stick to the sn package. On
subsamples of the entire population that I deal with, everything is fine.
However, on the total sample (difference in
Try maximizing the log-likelihood and using the log=TRUE argument to dmst.
(You have told us so little about what you are doing that we can but guess
at what you mean by `write an mle procedure': what is wrong with st.mle,
for example?)
On Tue, 28 Mar 2006, Konrad Banachewicz wrote:
Dear
On Tue, 28 Mar 2006 11:41:19 +0200, Konrad Banachewicz wrote:
please supply the ingredients needed to reproduce the problem that
you have faced (including the values of the parameters mu,P,alpha,nu,
among the rest)
best wishes,
Adelchi Azzalini
KB Dear All,
KB I am working with skewed-t
On 3/28/06, Prof Brian Ripley [EMAIL PROTECTED] wrote:
Try maximizing the log-likelihood and using the log=TRUE argument to dmst.
seems like dmst does not support this argument (the way e.g. dt does)
(You have told us so little about what you are doing that we can but guess
at what you
P is an identity matrix 240X240, mu and alpha are vectors of zeros
240X1, nu equals 10, so alltogether You need:
P - matrix(0,244,244)
diag(P) - 1
nu - 10
alpha - rep(0,244)
mu - rep(0,244)
require(sn)
t1 - rmst(1,mu,P, alpha, nu)
t2 - dmst(t1,mu,P,alpha,nu)
please supply the ingredients
You need to learn to supply adequate information. The current
version of sn *does* have such an argument, and I was careful to check.
So it seems that you are using an unstated obselete version of sn.
Do ugrade as the posting guide asked you to.
On Tue, 28 Mar 2006, Konrad Banachewicz wrote:
On Tue, 28 Mar 2006 13:11:02 +0200, Konrad Banachewicz wrote:
KB P is an identity matrix 240X240, mu and alpha are vectors of zeros
KB 240X1, nu equals 10, so alltogether You need:
KB P - matrix(0,244,244)
KB diag(P) - 1
KB nu - 10
KB alpha - rep(0,244)
KB mu - rep(0,244)
KB require(sn)
KB t1 -
On Tue, 28 Mar 2006 12:59:34 +0200, Konrad Banachewicz wrote:
KB On 3/28/06, Prof Brian Ripley [EMAIL PROTECTED] wrote:
KB
KB Try maximizing the log-likelihood and using the log=TRUE
KB argument to dmst.
KB
KB
KB seems like dmst does not support this argument (the way e.g. dt
KB does)
KB
