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forecastLSW (version 1.0)

Forecasting Routines for Locally Stationary Wavelet Processes

Description

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

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Version

Install

install.packages('forecastLSW')

Monthly Downloads

541

Version

1.0

License

GPL-2

Maintainer

Rebecca Killick

Last Published

April 25th, 2023

Functions in forecastLSW (1.0)

windanomaly

Eq. Pacific meridional wind anomaly index, Jan 1900 - June 2005
which.wavelet.best

Find out what wavelet is good for forecasting your series.
testforecast

Compare locally stationary forecasting with Box-Jenkins-type forecasting, by predicting the final values of a time series.
analyze.windanomaly

Analyzes the windanomaly data, see below for more details.
abmld2

Gross Value Added (GVA, Average) at basis prices: CP SA time series / second differenced series
forecastLSW-package

Forecasting for locally stationary (wavelet) time series based on the local partial autocorrelation function.
analyze.abmld2

Analyzes the abmld2 data, see below for more details.
forecastlpacf

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.
fp.forecast

Do automatic Box-Jenkins ARIMA fit and forecast.
forecastpanel

Function to produce a plot of data forecasts.
plot

Plot the results of forecasting using forecastlpacf
print

Prints a forecastlpacf object
summary

Print out summary information about a forecastlpacf object