xKfilter0: Kalman Filter - This script has been superseded by `Kfilter`

Description

Returns the filtered values for the basic time invariant state-space model; inputs are not allowed. NOTE: This script has been superseded by Kfilter. Note that scripts starting with an x are scheduled to be phased out.

Usage

xKfilter0(num, y, A, mu0, Sigma0, Phi, cQ, cR)

Value

xp: one-step-ahead state prediction
Pp: mean square prediction error
xf: filter value of the state
Pf: mean square filter error
like: the negative of the log likelihood
innov: innovation series
sig: innovation covariances
Kn: last value of the gain, needed for smoothing

Arguments

num: number of observations
y: data matrix, vector or time series
A: time-invariant observation matrix
mu0: initial state mean vector
Sigma0: initial state covariance matrix
Phi: state transition matrix
cQ: Cholesky-type decomposition of state error covariance matrix Q -- see details below
cR: Cholesky-type decomposition of observation error covariance matrix R -- see details below

Author

D.S. Stoffer

Details

NOTE: This script has been superseded by Kfilter

References

You can find demonstrations of astsa capabilities at FUN WITH ASTSA.

The most recent version of the package can be found at https://github.com/nickpoison/astsa/.

In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.

The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.