Extract the Log-Likelihood of a Revision Model

The returned object carries the degrees of freedom and effective number of observations used by the model, so stats::AIC() and stats::BIC() reproduce the values reported by summary().

Usage

# S3 method for class 'revision_model'
logLik(object, ...)

Arguments

object

A fitted model object inheriting from revision_model, such as a kk_model or a jvn_model.

...

Ignored.

Value

An object of class logLik.

See also

Other revision nowcasting: coef.revision_model(), fitted.revision_model(), jvn_nowcast(), kk_nowcast(), nobs.revision_model(), plot.revision_model(), predict.revision_model(), print.revision_model(), residuals.revision_model(), revision_model, states(), summary.revision_model(), vcov.revision_model()

Examples

df <- get_nth_release(
  tsbox::ts_span(
    tsbox::ts_pc(dplyr::filter(reviser::gdp, id == "US")),
    start = "1980-01-01"
  ),
  n = 0:1
)
df <- na.omit(dplyr::select(df, -c("id", "pub_date")))
fit <- kk_nowcast(df, e = 1, model = "KK", method = "MLE")
logLik(fit)
#> 'log Lik.' -100.8349 (df=5)
AIC(fit)
#> [1] 211.6698
BIC(fit)
#> [1] 230.988