This function provides a unified interface for implementations of the Kalman filter available in different packages.
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a numeric time series or vector.
a list containing the matrices of the state space model.
a character string indicating the implementation to be used.
a list containing optional arguments to be passed to the function that runs the Kalman filter.
logical. Currently ignored.
For some purposes such as testing, debugging or development of extensions, this function provides a useful unified interface for different implementations of the Kalman filter. In a production environment, the use of the original interfaces provided by each package is recommended since they sometimes provide further options or may incorporate further capabilities in the latest updates.
The elements in the argument
ss must be named in accordance with
the notation given in
char2numeric in package stsm
is a convenient way to create the argument
ss for those models already
defined in that package.
KF.args is empty, default values are defined depending on the interface
KF.version. The function
make.KF.args set default values
for those arguments that are explicitly defined in
KF.args. It also
checks that the arguments passed through
KF.args are correct and a warning
is given if any of them does not apply to the selected interface
KF.version: the option
StructTS applies the Kalman filter as
in the function
StructTS of the stats package. The remaining possible
values for this argument are the names of the package that contains
the Kalman filter interface.
Notes: (1) The package sppir is no longer maintained on CRAN and is not currently available here as an option. For old versions see sspir.
KF.version="dse" requires manually loading the package dse.
A list containing the output returned by each interface and the value
of the negative of the log-likelihood function in the element
Dethlefsen, C., Lundbye-Christensen, S. and Christensen A. L. (2012) R package version 0.2.10. sspir: State Space Models in R, http://CRAN.R-project.org/package=sspir.
Durbin, J. and Koopman, S. J. (2001). Time Series Analysis by State Space Methods. Oxford University Press.
Gilbert, P. D. (2013) R package version 2013.3-2. dse Brief User's Guide: Dynamic Systems Estimation, http://CRAN.R-project.org/package=dse.
Harvey, A. C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press.
Helske, J. (2012). R package version 0.9.11. KFAS: Kalman Filter and Smoother for Exponential family state space models., http://CRAN.R-project.org/package=KFAS.
Luethi, D., Erb, P. and Otziger, S. (2012) R package version 0.1.2. FKF: Fast Kalman Filter, http://CRAN.R-project.org/package=FKF.
Petris, G. (2013) R package version 1.1-3. dlm An R Package for Dynamic Linear Models, http://CRAN.R-project.org/package=dlm.
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# state space representation of a structural time series model # with arbitrary parameter values require("stsm") m <- stsm::stsm.model(model = "BSM", y = AirPassengers, transP = "StructTS", pars = c("var1" = 30, "var2" = 15, "var3" = 1, "var4" = 12)) ss <- stsm::char2numeric(m) # value of the likelihood using different interfaces and options KalmanFilter(y = m@y, ss = ss, KF.version = "KFKSDS", KF.args = list(P0cov = FALSE))$mloglik KalmanFilter(y = m@y, ss = ss, KF.version = "KFKSDS", KF.args = list(P0cov = TRUE))$mloglik # 'StructTS' does not include some constants KalmanFilter(y = m@y, ss = ss, KF.version = "StructTS")$mloglik
Loading required package: stsm  916.4979  857.4643  5.44563
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