xKsmooth0: Kalman Filter and Smoother - This script has been superseded...

In astsa: Applied Statistical Time Series Analysis

Kalman Filter and Smoother - This script has been superseded by Ksmooth

Description

Returns both the filtered values and smoothed values for the state-space model. NOTE: This script has been superseded by Ksmooth. Note that scripts starting with an x are scheduled to be phased out.

Usage

xKsmooth0(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NOTE: This script has been superseded by Ksmooth

Value

xs	state smoothers
Ps	smoother mean square error
x0n	initial mean smoother
P0n	initial smoother covariance
J0	initial value of the J matrix
J	the J matrices
xp	one-step-ahead prediction of the state
Pp	mean square prediction error
xf	filter value of the state
Pf	mean square filter error
like	the negative of the log likelihood
Kn	last value of the gain

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.