Description Usage Arguments Details Value Background References See Also Examples
Fits a skewt (ST) or multivariate skewt (MST) distribution to data, or
fits a linear regression model with (multivariate) skewt errors, using
maximum likelihood estimation. Functions copied from sn
CRAN library
v0.4.18 because they were later deprecated in that library.
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X 
a matrix of covariate values. If missing, a onecolumn matrix of
1's is created; otherwise, it must have the same number of rows of 
y 
a matrix (for 
freq 
a vector of weights. If missing, a vector of 1's is created;
otherwise it must have length equal to the number of rows of 
start 
for 
fixed.df 
a scalar value containing the degrees of freedom (df), if
these must be taked as fixed, or 
trace 
logical value which controls printing of the algorithm
convergence. If 
algorithm 
a character string which selects the numerical optimization
procedure used to maximize the loglikelihood function. If this string is set
equal to 
control 
this parameter is passed to the chose optimizer, either

If y
is a vector and it is supplied to mst.mle
, then it is
converted to a onecolumn matrix, and a scalar skewt distribution is
fitted. This is also the mechanism used by st.mle
which is simply an
interface to mst.mle
.
The parameter freq
is intended for use with grouped data, setting the
values of y
equal to the central values of the cells; in this case
the resulting estimate is an approximation to the exact maximum likelihood
estimate. If freq
is not set, exact maximum likelihood estimation is
performed.
likelihood estimation, use st.mle.grouped
.
Numerical search of the maximum likelihood estimates is performed in a
suitable reparameterization of the original parameters with aid of the
selected optimizer (nlminb
or optim
) which is supplied with
the derivatives of the loglikelihood function. Notice that, in case the
optimizer is optim
), the gradient may or may not be used, depending
on which specific method has been selected. On exit from the optimizer, an
inverse transformation of the parameters is performed. For a specific
description on the reparametrization adopted, see Section 5.1 and Appendix
B of Azzalini \& Capitanio (2003).
A list containing the following components:
call 
a string containing the calling statement. 
dp 
for

se 
a
list containing the components 
algorithm 
the list returned
by the chose optimizer, either 
The family of multivariate skewt distributions is an
extension of the multivariate Student's t family, via the introduction of a
shape
parameter which regulates skewness; when shape=0
, the
skewt distribution reduces to the usual t distribution. When df=Inf
the distribution reduces to the multivariate skewnormal one; see
dmsn
. See the reference below for additional information.
Azzalini, A. and Capitanio, A. (2003). Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t distribution. The full version of the paper published in abriged form in J.Roy. Statist. Soc. B 65, 367–389, is available at http://azzalini.stat.unipd.it/SN/seext.ps
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