loessf: Loess forecasting

In Techtonique/ahead: Time Series Forecasting with uncertainty quantification

Loess forecasting

Description

Loess forecasting

Usage

loessf(
  y,
  h = 5,
  level = 95,
  span = 0.75,
  degree = 2,
  type_pi = c("bootstrap", "blockbootstrap", "movingblockbootstrap"),
  b = NULL,
  B = 250,
  type_aggregation = c("mean", "median"),
  seed = 123
)

Arguments

y	A numeric vector or time series of class ts
h	Forecasting horizon
level	Confidence level for prediction intervals
span	the parameter which controls the degree of smoothing
degree	the degree of the polynomials to be used, normally 1 or 2. (Degree 0 is also allowed, but see stats::loess)
type_pi	Type of prediction interval currently (independent) "bootstrap", (circular) "blockbootstrap", or "movingblockbootstrap"
b	block length for circular block bootstrap
B	number of bootstrap replications
type_aggregation	Type of aggregation, ONLY for bootstrapping; either "mean" or "median"
seed	reproducibility seed

Value

An object of class "forecast"; a list containing the following elements:

model	A list containing information about the fitted model
method	The name of the forecasting method as a character string
mean	Point forecasts for the time series
lower	Lower bound for prediction interval
upper	Upper bound for prediction interval
x	The original time series
residuals	Residuals from the fitted model
sims	Model simulations for bootstrapping

Examples

par(mfrow = c(3, 1))

plot(loessf(Nile, h=20, level=95, B=10))

plot(loessf(Nile, h=20, level=95, B=10,
     type_pi = "blockbootstrap"))

plot(loessf(Nile, h=20, level=95, B=10,
     type_pi = "movingblockbootstrap"))

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