sim.hmm {hmm.discnp} | R Documentation |
Simulates one or more replicates of discrete data
from a model such as is fitted by the function hmm()
.
sim.hmm(nsim,tpm,Rho,ispd=NULL,yval=NULL)
nsim |
Vector of the lengths of the sequences of observations to be generated. |
tpm |
The transition probability matrix for the underlying hidden Markov
chain(s). Note that the rows of tpm must sum to 1.
Ignored if ncol(Rho)==1 .
|
Rho |
A matrix specifying the probability of an observation taking on
one of a set of possible values, given the state of the underlying
hidden Markov chain. Note that the columns of Rho must sum
to 1. If ncol(Rho)==1 the simulated data are i.i.d. from
the distribution specified by the single column of Rho .
|
ispd |
A vector specifying the initial state probability
distribution of the chain. If this is not specified it is
taken to be the stationary distribution of the chain, calculated
from tpm .
|
yval |
Vector of numbers or character strings constituting
the possible values of the observations. If not supplied it
is taken to equal 1:nrow(Rho) . |
If length(nsim)==1
then the value returned is a vector of
length nsim
. If length(nsim)>1
then the value returned
is a list of the same length as nsim
, each component of which
is an independent vector of simulated observations. The length
of component i
of this list is equal to nsim[i]
.
The values of the observations are entries of yval
.
Rolf Turner
r.turner@auckland.ac.nz
http://www.math.unb.ca/~rolf
hmm()
P <- matrix(c(0.7,0.3,0.1,0.9),2,2,byrow=TRUE) R <- matrix(c(0.5,0,0.1,0.1,0.3, 0.1,0.1,0,0.3,0.5),5,2) set.seed(42) y.num <- sim.hmm(rep(300,20),P,R) y.let <- sim.hmm(rep(300,20),P,R,yval=letters[1:5])