FIT - GARCH -----

#' Low-Level GARCH function for translating modeltime to forecast #' #' @param formula A dataframe of xreg (exogenous regressors) #' @param data A numeric vector of values to fit #' @param a The order of the non-seasonal auto-regressive (AR) terms. Often denoted "p" in pdq-notation. #' @param g The order of the non-seasonal auto-regressive (AR) terms. Often denoted "p" in pdq-notation. #' @param ... Additional arguments passed to forecast::Arima #' #' @export garch_fit_impl <- function(formula, data, a = 1, g = 1, ar_no_apply = NULL, ma_no_apply = NULL, period = "auto", ...)

# X & Y
others <- list(...) y <- all.vars(formula)[1]
 x <- attr(stats::terms(formula, data = data), "term.labels")outcome <- data[[y]]
predictors <- data %>% dplyr::select(dplyr::all_of(x))# INDEX & PERIOD
# Determine Period, Index Col, and Index
index_tbl <- modeltime::parse_index_from_data(predictors)
period    <- modeltime::parse_period_from_index(index_tbl, period)
idx_col   <- names(index_tbl)
idx       <- timetk::tk_index(index_tbl)# XREGS
# Clean names, get xreg recipe, process predictors
# xreg_recipe <- create_xreg_recipe(predictor, prepare = TRUE)
# xreg_matrix <- juice_xreg_recipe(xreg_recipe, format = "matrix")# FIT
outcome <- stats::ts(outcome, frequency = period)fit_garch <- tseries::garch(outcome, order = c(a, g), ...)# RETURN
modeltime::new_modeltime_bridge(
    class = "garch_fit_impl",    # Models
    models = list(
        model_1 = fit_garch
    ),    # Data - Date column (matches original), .actual, .fitted, and .residuals columns
    data = tibble::tibble(
        !! idx_col  := idx,
        .actual      =  as.numeric(outcome),
        .fitted      =  fit_garch$fitted.values[,1],
        .residuals   =  fit_garch$residuals
    ),    extras = list(
        y_var    = y,
        period   = period,
        otros    = others
    ),    # Description - Convert arima model parameters to short description
    desc = stringr::str_glue('GARCH ({fit_garch$order[1]}, {fit_garch$order[2]}) Model')
)

rugarch_fit_impl(
  formula,
  data,
  a = 1,
  g = 1,
  ar = 1,
  ma = 1,
  tune_by = NULL,
  period = "auto",
  ...
)

Arguments

formula	A dataframe of xreg (exogenous regressors)
data	A numeric vector of values to fit
a	The order of ARCH part
g	The order of GARCH part
ar	The order of the non-seasonal auto-regressive (AR) terms. Often denoted "p" in pdq-notation.
ma	The order of the non-seasonal auto-regressive (AR) terms. Often denoted "p" in pdq-notation.
tune_by	Parameter for tuning.
period	Period
...	Additional arguments passed to forecast::Arima

Value

A fitted model

Details

#' @export print.garch_fit_impl <- function(x, ...) print(x$models$model_1) invisible(x) Low-Level GARCH function for translating modeltime to forecast