Description Usage Arguments Details Value Note Examples
Solve a state space system using the Kalman Filter
1 | SS.solve(Z, F, H, Q, R, length.out, P0, beta0=0)
|
Z |
A T x n data matrix. |
F |
The state matrix. A scalar, or vector of length d, or a d x d matrix. When scalar, |
H |
The measurement matrix. Must be n x d. |
Q |
The state variance. A scalar, or vector of length d, or a d x d matrix. When scalar, |
R |
The measurement variance. A scalar, or vector of length n, or an n x n matrix. When scalar, |
length.out |
Scalar integer. |
P0 |
Initial a priori prediction error. |
beta0 |
Initial state value. A scalar, or a vector of length d. |
H
is the master argument from which system dimensionality is determined.
A named list.
B.apri |
A T x d matrix, the ith row of which is the best state estimate prior to observing data at time i. |
B.apos |
A T x d matrix, the ith row of which is the best state estimate given the observation at time i. |
For a definition of the system of interest, please see SSsimple
.
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