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Log-Likelihood of a VLMC with covariates

Source: R/covlmc_likelihood.R
logLik.covlmc.Rd

This function evaluates the log-likelihood of a VLMC with covariates fitted on a discrete time series.

Usage

# S3 method for covlmc
logLik(object, initial = c("truncated", "specific", "extended"), ...)

Arguments

object

the covlmc representation.

initial

specifies the likelihood function, more precisely the way the first few observations for which contexts cannot be calculated are integrated in the likelihood. Defaults to "truncated". See loglikelihood() for details.

...

additional parameters for logLik.

Value

an object of class logLik. This is a number, the log-likelihood of the (CO)VLMC with the following attributes:

  • df: the number of parameters used by the VLMC for this likelihood calculation

  • nobs: the number of observations included in this likelihood calculation

  • initial: the value of the initial parameter used to compute this likelihood

See also

loglikelihood()

Examples


## Likelihood for a fitted VLMC with covariates.
pc <- powerconsumption[powerconsumption$week == 5, ]
breaks <- c(
  0,
  median(powerconsumption$active_power, na.rm = TRUE),
  max(powerconsumption$active_power, na.rm = TRUE)
)
labels <- c(0, 1)
dts <- cut(pc$active_power, breaks = breaks, labels = labels)
dts_cov <- data.frame(day_night = (pc$hour >= 7 & pc$hour <= 17))
m_cov <- covlmc(dts, dts_cov, min_size = 5)
ll <- logLik(m_cov)
attributes(ll)
#> $nobs
#> [1] 1005
#> 
#> $df
#> [1] 5
#> 
#> $initial
#> [1] "truncated"
#> 
#> $class
#> [1] "logLik"
#>