4.8.6.3.2. statsmodels.tsa.kalmanf.kalmanfilter.kalmanfilter

statsmodels.tsa.kalmanf.kalmanfilter.kalmanfilter(F, A, H, Q, R, y, X, xi10, ntrain, history=False)

Returns the negative log-likelihood of y conditional on the information set

Assumes that the initial state and all innovations are multivariate Gaussian.

Parameters:

F : array-like

The (r x r) array holding the transition matrix for the hidden state.

A : array-like

The (nobs x k) array relating the predetermined variables to the observed data.

H : array-like

The (nobs x r) array relating the hidden state vector to the observed data.

Q : array-like

(r x r) variance/covariance matrix on the error term in the hidden state transition.

R : array-like

(nobs x nobs) variance/covariance of the noise in the observation equation.

y : array-like

The (nobs x 1) array holding the observed data.

X : array-like

The (nobs x k) array holding the predetermined variables data.

xi10 : array-like

Is the (r x 1) initial prior on the initial state vector.

ntrain : int

The number of training periods for the filter. This is the number of observations that do not affect the likelihood.

Returns:

likelihood

The negative of the log likelihood

history or priors, history of posterior

If history is True.

Notes

No input checking is done.