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dlm (version 0.7-1)

dlmSmooth: DLM smoothing

Description

The function apply Kalman smoother to compute smoothed values of the state vectors, together with their variance/covariance matrices.

Usage

dlmSmooth(modFilt, debug = FALSE)

Arguments

modFilt
An object of class "dlmFiltered", such as returned by dlmFilter
debug
If FALSE, faster C code will be used, otherwise all the computations will be performed in R.

Value

  • A list with components
  • sTime series (or matrix) of smoothed values of the state vectors. The series starts one time unit before the first observation.
  • U.SSee below.
  • D.STogether with U.S, it gives the SVD of the variances of the smoothing errors.

Details

The calculations are based on the singular value decomposition (SVD) of the relevant matrices. Variance matrices are returned in terms of their SVD.

References

Zhang, Y. and Li, X.R., Fixed-interval smoothing algorithm based on singular value decomposition, Proceedings of the 1996 IEEE International Conference on Control Applications.

See Also

See dlm for a description of dlm objects, dlmSvd2var to obtain a variance matrix from its SVD, dlmFilter for Kalman filtering, dlmMLE for maximum likelihood estimation, and dlmBSample for drawing from the posterior distribution of the state vectors.

Examples

Run this code
### See example for dlmFilter

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