Package: forecastLSW 1.1.1

forecastLSW: Forecasting Routines for Locally Stationary Wavelet Processes

Implementation to perform forecasting of locally stationary wavelet processes by examining the local second order structure of the time series.

Authors:Rebecca Killick [aut, cre], Matt Nunes [aut], Guy Nason [aut], Marina Knight [aut], Idris Eckley [ctb]

# Install 'forecastLSW' in R:

install.packages('forecastLSW', repos = c('https://adunaic.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

abml - Gross Value Added (GVA, Average) at basis prices: CP SA time series / second differenced series
abmld2 - Gross Value Added (GVA, Average) at basis prices: CP SA time series / second differenced series
windanomaly - Eq. Pacific meridional wind anomaly index, Jan 1900 - June 2005

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

Last updated from:ccd58d61da. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	128
source / vignettes	OK	194
linux-release-x86_64	OK	157
macos-release-arm64	OK	99
macos-oldrel-arm64	OK	91
windows-devel	OK	112
windows-release	OK	87
windows-oldrel	OK	89
wasm-release	OK	110

Help page	Topics
Forecasting for locally stationary (wavelet) time series based on the local partial autocorrelation function.	forecastLSW-package
Gross Value Added (GVA, Average) at basis prices: CP SA time series / second differenced series	abml abmld2
Analyzes the abmld2 data, see below for more details.	analyze.abmld2
Analyzes the windanomaly data, see below for more details.	analyze.windanomaly
Forecasts future values of the time series 'x' 'h'-steps ahead. (for the specified horizon 'h') using the lpacf to decide the dimension of the generalized Yule-Walker equations.	dforecastlpacf forecastlpacf
Function to produce a plot of data forecasts.	forecastpanel
Do automatic Box-Jenkins ARIMA fit and forecast.	fp.forecast
Plot the results of forecasting using 'forecastlpacf'	plot.forecastlpacf
Prints a 'forecastlpacf' object	print.forecastlpacf
Print out summary information about a 'forecastlpacf' object	summary.forecastlpacf
Compare locally stationary forecasting with Box-Jenkins-type forecasting, by predicting the final values of a time series.	testforecast
Find out what wavelet is good for forecasting your series.	which.wavelet.best
Eq. Pacific meridional wind anomaly index, Jan 1900 - June 2005	windanomaly