Fits a simple univariate state space model, x[t] = alpha + phi x[t-1] + w[t],
and y[t] = A x[t] + v[t]. The parameters alpha, phi, sigma[w] and sigma[v]
are estimated; parameter phi may be fixed. State predictions and smoothers
and corresponding error variances are evaluated at the estimates. The sample
size must be at least 20.
Usage
ssm(y, A, phi, alpha, sigw, sigv, fixphi = FALSE)
Value
At the MLEs, these are returned invisibly:
Xp
time series - state prediction, \(x_t^{t-1}\)
Pp
corresponding MSPEs, \(P_t^{t-1}\)
Xf
time series - state filter, \(x_t^t\)
Pf
corresponding MSEs, \(P_t^t\)
Xs
time series - state smoother, \(x_t^n\)
Ps
corresponding MSEs, \(P_t^n\)
Arguments
y
data
A
measurement value (fixed constant)
phi
initial value of phi, may be fixed
alpha
initial value for alpha
sigw
initial value for sigma[w]
sigv
initial value for sigma[v]
fixphi
if TRUE, the phi parameter is fixed
Author
D.S. Stoffer
Details
The script works for a specific univariate state space model.
The initial state conditions use a default calculation and cannot be specified.
The parameter estimates are printed and the script returns the state predictors and
smoothers.
References
You can find demonstrations of astsa capabilities at
FUN WITH ASTSA.