toSSChol {dse}R Documentation

Convert to Non-Innovation State Space Model


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Convert to a non-innovations state space representation using the given matrix (Om) as the measurement noise covariance. Om would typically be an estimate of the output noise, such as returned in $estimates$cov of the function l (l.SS or l.ARMA). This assumes that the noise processes in the arbitrary SS representation are white and uncorrelated.


    toSSChol(model, ...)
    ## S3 method for class 'TSmodel'
toSSChol(model, Om=diag(1,nseriesOutput(model)), ...)
    ## S3 method for class 'TSestModel'
toSSChol(model, Om=NULL, ...)



An object of class TSmodel.


a matrix to be used as the measurement noise covariance. If Om is not supplied and model is of class TSestModel then model$estimates$cov is used. Otherwise, Om is set to the identity matrix.


arguments to be passed to other methods.


Convert to a non-innovations SS representation using a Cholesky decomposition of Om as the coefficient matrix of the output noise.


An object of class 'SS' 'TSmodel' containing a state space model which is not in innovations form.

See Also



    data("", package="dse")
    model <- estVARXls(
    model <- toSSChol(model)

[Package dse version 2020.2-1 Index]