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
- k_posdef¶
The dimension of a guaranteed positive definite covariance matrix describing the shocks in the measurement equation.
- Type:
- dtype¶
Datatype of representation matrices
- Type:
dtype
- shapes¶
A dictionary recording the shapes of each of the representation matrices as tuples.
- Type:
dictionary of name:tuple
- endog¶
The observation vector.
- Type:
ndarray
- design¶
The design matrix, \(Z\).
- Type:
ndarray
- obs_intercept¶
The intercept for the observation equation, \(d\).
- Type:
ndarray
- obs_cov¶
The covariance matrix for the observation equation \(H\).
- Type:
ndarray
- transition¶
The transition matrix, \(T\).
- Type:
ndarray
- state_intercept¶
The intercept for the transition equation, \(c\).
- Type:
ndarray
- selection¶
The selection matrix, \(R\).
- Type:
ndarray
- state_cov¶
The covariance matrix for the state equation \(Q\).
- Type:
ndarray
- 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
- 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)Update model Representation
