array of univariate or multivariate series with dimension T*N.samples*d.
T: number of time steps of each sample, N.samples: number of realisations of the same stationary process, d: dimension.
theta
model's parameter; object of class MSAR. See also init.theta.MSAR.
FB
Forward-Backward results, obtained by calling Estep.MSAR function
covar
transitions covariates
method
permits to choice the optimization algorithm. default is "ucminf", other possible choices are "BFGS" or "L-BFGS-B"
ARfix
if TRUE the AR parameters are not estimated, they stay fixed at their initial value.
Value
List containing
..$A0intercepts
..$AAR coefficients
..$sigmavariance of innovation
..$priorprior probabilities
..$transmattransition matrix
..$par.transtransitions parameters
References
Ailliot P., Monbet V., (2012), Markov switching autoregressive models for wind time series. Environmental Modelling & Software, 30, pp 92-101.