Log-likelihood of a filtration or an estimate

For a qpm_filtration this is the Kalman-filter log-likelihood of the data under the calibrated model, with zero degrees of freedom (nothing was estimated). For a qpm_estimate it is the log-likelihood at the posterior mode (or at the maximum for method = "mle"), with degrees of freedom equal to the number of estimated parameters — so stats::AIC() and stats::BIC() work.

Usage

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

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

Arguments

object

A qpm_filtration or qpm_estimate.

...

Unused.

Value

An object of class logLik.

Examples

sol <- qpm_solve(qpm_template("bkl"))
obs <- simulate(sol, nsim = 40, seed = 1, burn = 20)
fit <- qpm_filter(sol, obs[, c("period", "pi", "i", "q")])
logLik(fit)
#> 'log Lik.' -195.152 (df=0)