dlm: dlmLL – R documentation

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dlmLL

Log likelihood evaluation for a state space model

Function that computes the log likelihood of a state space model.

dlmLL(y, mod, debug=FALSE)

`y`	a vector, matrix, or time series of data.
`mod`	an object of class `"dlm"`, or a list with components `m0`, `C0`, `FF`, `V`, `GG`, `W` defining the model and the parameters of the prior distribution.
`debug`	if `debug=TRUE`, the function uses R code, otherwise it uses faster C code.

The calculations are based on singular value decomposition. Missing values are allowed in y.

The function returns the negative of the loglikelihood.

The observation variance V in mod must be nonsingular.

Durbin and Koopman, Time series analysis by state space methods, Oxford University Press, 2001.

##---- See the examples for dlmMLE ----

Bayesian and Likelihood Analysis of Dynamic Linear Models

v1.1-5

GPL (>= 2)

Authors

Giovanni Petris [aut, cre], Wally Gilks [ctb] (Author of original C code for ARMS)

Initial release

2018-05-30