coefficients.fitted_dlm: coefficients.fitted_dlm

In kDGLM: Bayesian Analysis of Dynamic Generalized Linear Models

coefficients.fitted_dlm

Description

This method is wrapper for the coef method.

Usage

## S3 method for class 'fitted_dlm'
coefficients(object, ...)

Arguments

object	A fitted_dlm object.
...	Arguments passed to coef.

Value

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.

See Also

coef.fitted_dlm

kDGLM documentation built on April 4, 2025, 4:44 a.m.