Interface DlmFitResult

Smoothed covariances [row][col][time]

Initial state covariance (scaled)

Filtered covariances [row][col][time]

Class identifier

Innovation covariances

Observation vector F (1×m flattened)

State transition matrix G (m×m)

-2 * log likelihood

Mean absolute percentage error

Mean squared error

Number of observations

Scaled residuals

Raw residuals

Standardized residuals

Residual variance

Sum of squared residuals

Innovations

Observation noise standard deviations

State noise covariance W (m×m)

Smoothed state means [state_dim][time]

Initial state mean (after first smoother pass)

Filtered state means [state_dim][time]

Smoothed state standard deviations [time][state_dim]

Covariates matrix: XX[t] is the covariate row at time t (empty array when no covariates)

Observations

Filter predictions

Prediction standard deviations