est_con_multinominal_c: Estimating log likelihood in Condition Stage

Description

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
)

Value

Returns the log likelihood as a single numeric value.

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.

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