itsmr-package {itsmr}

Time Series Analysis Using the Innovations Algorithm

Description

Provides functions for modeling and forecasting time series data. Forecasting is based on the innovations algorithm. A description of the innovations algorithm can be found in the textbook Introduction to Time Series and Forecasting by Peter J. Brockwell and Richard A. Davis.

Details

Package:	itsmr
Type:	Package
Version:	1.10
Date:	2022-07-27
License:	FreeBSD
LazyLoad:	yes
URL:	https://georgeweigt.github.io/itsmr-refman.pdf

Author(s)

George Weigt
Maintainer: George Weigt <[e-mail]>

References

Brockwell, Peter J., and Richard A. Davis. Introduction to Time Series and Forecasting. 2nd ed. Springer, 2002.

Examples

plotc(wine)

## Define a suitable data model
M = c("log","season",12,"trend",1)

## Obtain residuals and check for stationarity
e = Resid(wine,M)
test(e)

## Define a suitable ARMA model
a = arma(e,p=1,q=1)

## Obtain residuals and check for white noise
ee = Resid(wine,M,a)
test(ee)

## Forecast future values
forecast(wine,M,a)