Description Usage Arguments Value Author(s) See Also Examples
View source: R/Mstep.classif.R
fit an AR model for each class of C by maximum likelihood method.
1 | Mstep.classif(data, C, order,sigma.diag=FALSE)
|
data |
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. |
C |
Class sequence |
order |
order of AR models (all models will have the same order) |
sigma.diag |
if TRUE the covariance matrices will be diagonal (default FALSE) |
list containing
A0 |
intercept |
A |
AR coefficients |
sigma |
variance of innovation |
LL |
log likelihood |
Valerie Monbet, valerie.monbet@univ-rennes1.fr
fit.MSAR
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