Fast computation of the multivariate Student's t density.
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X |
matrix n by d where each row is a d dimensional random vector. Alternatively |
mu |
vector of length d, representing the mean of the distribution. |
sigma |
scale matrix (d x d). Alternatively it can be the cholesky decomposition
of the scale matrix. In that case isChol should be set to TRUE. Notice that ff the degrees of
freedom (the argument |
df |
a positive scalar representing the degrees of freedom. |
log |
boolean set to true the logarithm of the pdf is required. |
ncores |
Number of cores used. The parallelization will take place only if OpenMP is supported. |
isChol |
boolean set to true is |
There are in fact many candidates for the multivariate generalization of Student's t-distribution, here we use
the parametrization described here https://en.wikipedia.org/wiki/Multivariate_t-distribution. NB: at the moment
the parallelization does not work properly on Solaris OS when ncores>1
. Hence, dmvt()
checks if the OS
is Solaris and, if this the case, it imposes ncores==1
.
A vector of length n where the i-the entry contains the pdf of the i-th random vector.
Matteo Fasiolo <matteo.fasiolo@gmail.com>
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