This function computes log, quadrtic and ranked probability scores for Poisson and Generalized Poisson models.
cocoSoc(
data,
models = "all",
print.progress = TRUE,
max_x_score = 50,
julia = FALSE,
...
)A list of class "cocoSoc" containing:
A list of fitted model objects.
A list of score objects for each model.
A data frame containing the logarithmic, quadratic, and ranked probability scores for each model.
A numeric vector containing the data to be used for modeling
A character string specifying which models to use. Default is "all", which uses both Poisson and GP models.
A logical value indicating whether to print progress messages (Default: TRUE).
An integer which is used as the maximum count for the computation
of the score (defaul: 50)
if TRUE, cocoSoc is run with julia (default: FALSE)
Additional arguments to be passed to the cocoReg function.
Manuel Huth
Supports model selection by computing score over a range of models while maintaining a common sample and a common specification.