# 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
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