In nelson16silva/wavdrcast: Wavelet-Based Direct Multistep Forecast

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

wavdrcast

This package provides forecasts of time series using a direct multistep model where regressors can be composed by wavelet-based signal estimation. A functional available in wavdrcast allows one to choose a good wavelet specification for sinal extraction considering the forecast criterion. The scope is not limited to wavelet regressors, however. In general, any other data set can be used as an exogenous variable, including AR components of the time series. This can be interesting when one is comparing the forecast property of core inflation measure or output gap estimators.

Installation

You can install the development version from GitHub with:

# install.packages("wavdrcast")
devtools::install_github("nelson16silva/wavdrcast", build_vignettes = TRUE)

Example

library(wavdrcast)

See wdrcast's vignette:

vignette("intro", package = "wavdrcast")
browseVignettes("wavdrcast")

nelson16silva/wavdrcast documentation built on April 25, 2021, 7:03 a.m.