SS.solve.tv: Optimal Estimation

In SSsimple: State Space Models

Description

Solve a time-varying state space system using the Kalman Filter

Usage

SS.solve.tv(Z, F, H, Q, R, length.out, P0, beta0)

Arguments

Z	A T x n data matrix
F	A list of d x d matrices.
H	A list of n x d matrices.
Q	A list of d x d matrices.
R	A list of n x n matrices.
length.out	A scalar integer.
P0	Initial a priori prediction error.
beta0	Initial state value. A scalar, or a vector of length d.

Details

This function is a more general, and slower, implementation of SS.solve. This function can also accept arguments in non-time-varying fashion (a la SS.solve).

Value

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.

See Also

SS.solve

SSsimple documentation built on Dec. 7, 2019, 9:06 a.m.