fitforecast: Fit and forecast for benchmarking purposes

In Techtonique/ahead: Time Series Forecasting with uncertainty quantification

Fit and forecast for benchmarking purposes

Description

Fit and forecast for benchmarking purposes

Usage

fitforecast(
  y,
  h = NULL,
  pct_train = 0.9,
  pct_calibration = 0.5,
  method = c("thetaf", "arima", "ets", "te", "tbats", "tslm", "dynrmf", "ridge2f",
    "naive", "snaive"),
  level = 95,
  B = 1000L,
  seed = 17223L,
  graph = TRUE,
  conformalize = FALSE,
  type_calibration = c("splitconformal", "cv1", "loocv"),
  gap = 3L,
  agg = c("mean", "median"),
  vol = c("constant", "garch"),
  type_sim = c("kde", "surrogate", "bootstrap"),
  ...
)

Arguments

y	A univariate time series of class ts
h	Forecasting horizon (default is NULL, in that case, pct_train and pct_calibration are used)
pct_train	Percentage of data in the training set, when h is NULL
pct_calibration	Percentage of data in the calibration set for conformal prediction
method	For now "thetaf" (default), "arima", "ets", "tbats", "tslm", "dynrmf" (from ahead), "ridge2f" (from ahead), "naive", "snaive"
level	Confidence level for prediction intervals in %, default is 95
B	Number of bootstrap replications or number of simulations (yes, 'B' is unfortunate)
seed	Reproducibility seed
graph	Plot or not?
conformalize	Calibrate or not?
type_calibration	"splitconformal" (default conformal method), "cv1" (do not use), "loocv" (do not use)
gap	length of training set for loocv conformal (do not use)
agg	"mean" or "median" (aggregation method) for
vol	"constant" or "garch" (type of volatility modeling for calibrated residuals)
type_sim	"kde", "surrogate", "bootstrap" (type of simulation for calibrated residuals)
...	additional parameters

Value

an object of class 'forecast' with additional information

Examples

par(mfrow=c(2, 2))
obj1 <- ahead::fitforecast(AirPassengers)
obj2 <- ahead::fitforecast(AirPassengers, conformalize = TRUE)
plot(AirPassengers)
plot(obj1)
obj2$plot()
obj2$plot("simulations")

Techtonique/ahead documentation built on Nov. 24, 2024, 10:33 a.m.