Solve a time-varying state space system using the Kalman Filter
SS.solve.tv(Z, F, H, Q, R, length.out, P0, beta0)A T x n data matrix
A list of d x d matrices.
A list of n x d matrices.
A list of d x d matrices.
A list of n x n matrices.
A scalar integer.
Initial a priori prediction error.
Initial state value. A scalar, or a vector of length d.
A named list.
A T x d matrix, the ith row of which is the best state estimate prior to observing data at time i.
A T x d matrix, the ith row of which is the best state estimate given the observation at time i.
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).