eval_dlm_log_like function

Auxiliary function for evaluating the prior density of a DLM

Evaluates the prior density for a set of parameters theta in a DLM. The structure of the DLM is taken to be that of the fitted_dlm object passed as input.

eval_dlm_log_like(theta, model, lin.pred = FALSE)

Arguments

• theta: Matrix: A matrix representing the set of parameter for which to evaluate the density. Its size should be n x t, where n is the number of latent states and t is the length of the time series;
• model: fitted_dlm: A fitted_dlm object.
• lin.pred: boolean: A flag indicating if theta represents the linear predictors.

Returns

A scalar representing the log likelihood evaluated at theta.

Examples

data <- c(AirPassengers)

level <- polynomial_block(rate = 1, order = 2, D = 0.95)
season <- harmonic_block(rate = 1, order = 2, period = 12, D = 0.975)

outcome <- Poisson(lambda = "rate", data = data)

fitted.data <- fit_model(level, season,
  AirPassengers = outcome
)
eval_dlm_log_like(fitted.data$mts, fitted.data)