View source: R/RHmm-HyperNew.R
asymptoticIterSimCovMat | R Documentation |
This ‘new’ function computes the empirical asymptotic covariance matrix of the fitted HMM.
asymptoticIterSimCovMat(HMM, obs, nSimul, verbose=FALSE, oldCovMat=NULL)
HMM |
a HMMClass or HMMFitClass object |
obs |
A vector, a matrix, a data frame, a list of vectors or a list of matrices of observations. See HMMFit. |
nSimul |
The number of simulation |
verbose |
A boolean. if true, displays some informations. Default false. |
oldCovMat |
An object containing
where |
An object with the same attributes than ‘oldCovMat’ parameter.
This is an “experimental” method. The HMM model is simulated nSimul times then fitted and the empirical covariance matrix is computed.
setAsymptoticCovMat
, asymptoticCov
# Fit a 3 states 1D-gaussian model
data(n1d_3s)
Res <- HMMFit(obs_n1d_3s, nStates=3)
# First 10 computations of covariance matrix
Cov <- asymptoticIterSimCovMat(Res, obs_n1d_3s, 10)
# 10 more computations of covariance matrix
Cov <- asymptoticIterSimCovMat(Res, obs_n1d_3s, 10, verbose=TRUE, oldCovMat=Cov)
Res<-setAsymptoticCovMat(Res, Cov$cov)
summary(Res)
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