cocoSoc {coconots}R Documentation

Computes Scores for Various Models Maintaining a Common Sample

Description

This function computes log, quadrtic and ranked probability scores for Poisson and Generalized Poisson models.

Usage

cocoSoc(
  data,
  models = "all",
  print.progress = TRUE,
  max_x_score = 50,
  julia = FALSE,
  ...
)

Arguments

data

A numeric vector containing the data to be used for modeling

models

A character string specifying which models to use. Default is '"all"', which uses both Poisson and GP models.

print.progress

A logical value indicating whether to print progress messages (Default: 'TRUE').

max_x_score

An integer which is used as the maximum count for the computation of the score (defaul: '50')

julia

if TRUE, cocoSoc is run with julia (default: FALSE)

...

Additional arguments to be passed to the 'cocoReg' function.

Details

Supports model selection by computing score over a range of models while maintaining a common sample and a common specification.

Value

A list of class '"cocoSoc"' containing:

fits

A list of fitted model objects.

scores_list

A list of score objects for each model.

scores_df

A data frame containing the logarithmic, quadratic, and ranked probability scores for each model.

Author(s)

Manuel Huth


[Package coconots version 2.0.0 Index]