xKfilter0 function

Kalman Filter - This script has been superseded by Kfilter

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 NOTE: This script has been superseded by Kfilter.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.

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

Returns

• 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

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/.

Author(s)

D.S. Stoffer

Details

NOTE: This script has been superseded by Kfilter