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

Number of observations.

Type:int
k_endog

The dimension of the observation series.

Type:int
k_states

The dimension of the unobserved state process.

Type:int
k_posdef

The dimension of a guaranteed positive definite covariance matrix describing the shocks in the measurement equation.

Type:int
dtype

Datatype of representation matrices

Type:dtype
prefix

BLAS prefix of representation matrices

Type:str
shapes

A dictionary recording the shapes of each of the representation matrices as tuples.

Type:dictionary of name:tuple
endog

The observation vector.

Type:array
design

The design matrix, \(Z\).

Type:array
obs_intercept

The intercept for the observation equation, \(d\).

Type:array
obs_cov

The covariance matrix for the observation equation \(H\).

Type:array
transition

The transition matrix, \(T\).

Type:array
state_intercept

The intercept for the transition equation, \(c\).

Type:array
selection

The selection matrix, \(R\).

Type:array
state_cov

The covariance matrix for the state equation \(Q\).

Type:array
missing

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.

Type:array of bool
nmissing

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.

Type:array of int
time_invariant

Whether or not the representation matrices are time-invariant

Type:bool
initialization

Kalman filter initialization method.

Type:Initialization object
initial_state

The state vector used to initialize the Kalamn filter.

Type:array_like
initial_state_cov

The state covariance matrix used to initialize the Kalamn filter.

Type:array_like

Methods

update_representation(model)