Estimating log likelihood in Condition Stage — est_con_multinominal

Function written in C++ estimating the log likelihood of a given parameter set during the condition stage.

Usage

est_con_multinominal_c(
  observations,
  anchor,
  max_iter = 500000L,
  step_size = 1e-04,
  cr_rel_change = 1e-12,
  n_random_starts = 10L,
  fast = TRUE,
  trace = FALSE
)

Arguments

observations: NumericVector containing the frequency of the categories.
anchor: Integer ranging between 1 and the number of categories. Anchor defines the reference category. That is the category with the highest probability according to the assumption of weak superiority.
max_iter: Integer specifying the maximal number of iterations for each random start.
step_size: Double for specifying the size for increasing or decreasing the probabilities during the estimation. This value should not be less than 1e-3.
cr_rel_change: Double for defining when the estimation should stop. That is, if the change in log-likelihood is smaller as this value the estimation stops.
n_random_starts: Integer for the number of random start.
fast: Bool If TRUE a fast estimation is applied. This option ignored all other parameters. If FALSE the estimation described in Berding and Pargmann (2022) is used. Default is TRUE.
trace: Bool TRUE if information about the progress of estimation should be printed to the console. FALSE if not desired.

Value

Returns the log likelihood as a single numeric value.

References

Berding, Florian, and Pargmann, Julia (2022).Iota Reliability Concept of the Second Generation.Measures for Content Analysis Done by Humans or Artificial Intelligences. Berlin: Logos. https://doi.org/10.30819/5581