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itsmr (version 1.9)

itsmr-package: 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.

Arguments

Author

George Weigt
Maintainer: George Weigt <g808391@icloud.com>

Details

Package:itsmr
Type:Package
Version:1.9
Date:2018-09-06
License:FreeBSD
LazyLoad:yes
URL:http://eigenmath.org/itsmr-refman.pdf

References

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

Examples

Run this code
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)

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