ppd_gamlss: Fit 'gamlss'-type semi-parametric models
In jbrowell/ProbCast: Flexible Probabilistic Forecasting

ppd_gamlss

R Documentation

Fit `gamlss`-type semi-parametric models

Description

This function is a wrapper for the function gamlss, which fits semi-parametric regression models for predictive distributions with up to four parameters (location, scale, shape1, shape2).

Usage

ppd_gamlss(
  data,
  formula,
  cv_folds = NULL,
  sigma.formula = ~1,
  nu.formula = ~1,
  tau.formula = ~1,
  family = gamlss.dist::NO(),
  cores = 1,
  pckgs = NULL,
  save_models_path = NULL,
  ... = 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.
`cv_folds`	Control for cross-validation if not supplied in `data`.
`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.
`cores`	the number of available cores. Defaults to one, i.e. no parallelisation, although in this case the user must still specify `pckgs` if applicable.
`pckgs`	specify additional packages required for each worker (e.g. c("data.table") if data stored as such).
`save_models_path`	Path to save models. Model details and file extension pasted onto this string.
`...`	Additional 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.