statsmodels.tsa.statespace.representation.FrozenRepresentation

class statsmodels.tsa.statespace.representation.FrozenRepresentation(model)[source]

Frozen Statespace Model

Takes a snapshot of a Statespace model.

Parameters:

model : Representation

A Statespace representation

Attributes

nobs (int) Number of observations.
k_endog (int) The dimension of the observation series.
k_states (int) The dimension of the unobserved state process.
k_posdef (int) The dimension of a guaranteed positive definite covariance matrix describing the shocks in the measurement equation.
dtype (dtype) Datatype of representation matrices
prefix (str) BLAS prefix of representation matrices
shapes (dictionary of name:tuple) A dictionary recording the shapes of each of the representation matrices as tuples.
endog (array) The observation vector.
design (array) The design matrix, Z.
obs_intercept (array) The intercept for the observation equation, d.
obs_cov (array) The covariance matrix for the observation equation H.
transition (array) The transition matrix, T.
state_intercept (array) The intercept for the transition equation, c.
selection (array) The selection matrix, R.
state_cov (array) The covariance matrix for the state equation Q.
missing (array of bool) An array of the same size as endog, filled with boolean values that are True if the corresponding entry in endog is NaN and False otherwise.
nmissing (array of int) An array of size nobs, where the ith entry is the number (between 0 and k_endog) of NaNs in the ith row of the endog array.
time_invariant (bool) Whether or not the representation matrices are time-invariant
initialization (str) Kalman filter initialization method.
initial_state (array_like) The state vector used to initialize the Kalamn filter.
initial_state_cov (array_like) The state covariance matrix used to initialize the Kalamn filter.

Methods

update_representation(model)

Methods

update_representation(model)