Description Usage Arguments Details Value References See Also Examples
Generate random sample from a specified mixture of unrestricted multivariate skew t distribution
1 2 3 |
g |
a scalar specifying the number of components in the mixture model |
n |
either a positive integer specifying the total number of points to be generated
or a vector (of length |
mu |
for |
sigma |
for |
delta |
for |
dof |
for |
pro |
the mixing proportions; for |
known |
a list containing the parameters of the model.
If specified, it overwrites the values of |
rmst
generates a sample n
multivariate skew t (MST) variables.
rfmmst
generates a mixture of MST samples.
Note that model parameters can be passed to rmst
and rfmmst
through the argument known
or listed as individual arguments.
If both methods of input were used, the parameters specified in known
will be used.
rmst
returns an n
by p
numeric matrix of generated data.
rfmmst
returns an n
by p+1
numeric matrix of genertaed data.
The first p
gives the coordinates of the generated data.
The last column specifies which component each data point is generated from.
Lee S, McLachlan G (2011). On the fitting of mixtures of multivariate skew t-distributions via the EM algorithm. arXiv:1109.4706 [stat.ME]
Lee, S. and McLachlan, G.J. (2014) Finite mixtures of multivariate skew t-distributions: some recent and new results. Statistics and Computing, 24, 181-202.
Lee, S. and McLachlan, G.J. (2013) EMMIXuskew: An R
package for
fitting mixtures of multivariate skew t-distributions via the EM algorithm.
Journal of Statistical Software, 55(12), 1-22.
URL http://www.jstatsoft.org/v55/i12/.
1 2 3 4 5 6 7 8 9 10 11 12 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
rfmmst(1,500, c(1,2), diag(2), c(-1,1), 4, 1)
obj <- list()
obj$mu <- list(c(17,19), c(5,22), c(6,10))
obj$sigma <- list(diag(2), matrix(c(2,0,0,1),2), matrix(c(3,7,7,24),2))
obj$delta <- list(c(3,1.5), c(5,10), c(2,0))
obj$dof <- c(1, 2, 3)
obj$pro <- c(0.25, 0.25, 0.5)
rfmmst(3, 250, obj$mu, obj$sigma, obj$delta, obj$dof, obj$pro)
rfmmst(3, 500, known=obj)
|
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