On Apr 2, 2011, at 1:15 PM, statfan wrote:
The definition of the "mean vector" is essentially what my question
boils
down to. In the functions details, the author states
"We sample x ~ T(mean, Sigma, df) subject to the rectangular
truncation
lower <= x <= upper. Currently, two random numb
The definition of the "mean vector" is essentially what my question boils
down to. In the functions details, the author states
"We sample x ~ T(mean, Sigma, df) subject to the rectangular truncation
lower <= x <= upper. Currently, two random number generation methods are
implemented: rejection sa
On Apr 2, 2011, at 11:06 AM, statfan wrote:
I am sampling from the truncated multivariate student t distribution
"rtmvt"
in the package {tmvtnorm}. My question is about the mean vector. Is
it
possible to define a mean vector outside of the truncated region?
Thank you
in advance for any h
I am sampling from the truncated multivariate student t distribution "rtmvt"
in the package {tmvtnorm}. My question is about the mean vector. Is it
possible to define a mean vector outside of the truncated region? Thank you
in advance for any help.
--
View this message in context:
http://r.78969
Dear R users,
I am working on the Value at Risk (VaR) for the Operational risk. For a given
loss data, we try to fit some statistical distributions using
Kolmogorov-Smirnov (KS) test and A-D test and then for fitted distribution
using the estimated parameters, the losses are simulated and the
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