xKsmooth0 {astsa}

Kalman Filter and Smoother - This script has been superseded by Ksmooth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 NOTE: This script has been superseded by Ksmooth.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NOTE: This script has been superseded by Ksmooth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/.