This method is wrapper for the coef method.
# S3 method for fitted_dlm
coefficients(object, ...)A list containing:
data data.frame: A table with the model evaluated at each observed time.
theta.mean matrix: The mean of the latent states at each time. Dimensions are n x t, where t is the size of t.eval and n is the number of latent states.
theta.cov array: A 3D-array containing the covariance matrix of the latent states at each time. Dimensions are n x n x t, where t is the size of t.eval and n is the number of latent states.
lambda.mean matrix: The mean of the linear predictor at each time. Dimensions are k x t, where t is the size of t.eval and k is the number of linear predictors.
lambda.cov array: A 3D-array containing the covariance matrix for the linear predictor at each time. Dimensions are k x k x t, where t is the size of t.eval and k is the number of linear predictors.
log.like, mae, mase, rae, mse, interval.score: The metric value at each time.
conj.param list: A list containing, for each outcome, a data.frame with the parameter of the conjugated distribution at each time.
A fitted_dlm object.
Arguments passed to coef.
coef.fitted_dlm