xKfilter0: Kalman Filter - This script has been superseded by 'Kfilter'

In astsa: Applied Statistical Time Series Analysis

Kalman Filter - This script has been superseded by Kfilter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 NOTE: This script has been superseded by Kfilter.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)

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

Details

NOTE: This script has been superseded by Kfilter

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

Author(s)

D.S. Stoffer

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/.

astsa documentation built on May 29, 2024, 10:29 a.m.