Para_gamlss: Fit 'gamlss'-type semi-parametric models (depreciated)

In jbrowell/ProbCast: Flexible Probabilistic Forecasting

Fit gamlss-type semi-parametric models (depreciated)

Description

This function is now depreciated and may be removed in future versions of this package. Use ppd_gamlss() instead.

Usage

Para_gamlss(
  data,
  formula,
  sigma.formula = ~1,
  nu.formula = ~1,
  tau.formula = ~1,
  family = gamlss.dist::NO(),
  parallel = F,
  cores = NULL,
  pckgs = NULL,
  ...
)

Arguments

data	A data.frame containing target and explanatory variables. May optionally contain a column called "kfold" with numbered/labeled folds and "Test" for test data.
formula	A formula object with the response on the left of an ~ operator, and the terms, separated by + operators, on the right.
sigma.formula	A formula object for fitting a model to the sigma parameter, as in the formula above.
nu.formula	A formula object for fitting a model to the nu parameter, as in the formula above.
tau.formula	A formula object for fitting a model to the tau parameter, as in the formula above.
family	A gamlss.family object, which is used to define the distribution and the link functions of the various parameters.
parallel	boolean parallelize model fitting process? Parallelisation is over cross-validation folds.
cores	if parallel is TRUE then number of available cores
pckgs	if parallel is TRUE then specify packages required for each worker (e.g. c("data.table) if data stored as such)
...	Additonal arguments passed to gamlss().

Details

See ?gamlss for additional details and options.

Value

A list of gamlss models with class PPD. Each list element corresponds to a cross-validation fold and contains a gamlss model trained on all other folds.

Author(s)

Jethro Browell, [e-mail]; Ciaran Gilbert, [e-mail]

jbrowell/ProbCast documentation built on July 20, 2024, 1:53 p.m.