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, |
... |
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