itsmr: Time series analysis package for students

This package provides a subset of the functionality found in the Windows-based program ITSM. The intended audience is students using the textbook "Introduction to Time Series and Forecasting" by Peter J. Brockwell and Richard A. Davis.

AuthorGeorge Weigt
Date of publication2011-11-13 09:12:27
MaintainerGeorge Weigt <>

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Man pages

aacvf: Autocovariance of ARMA model

acvf: Autocovariance of data

airpass: Number of international airline passengers, 1949 to 1960

arar: Forecast using ARAR algorithm

ar.inf: Compute AR infinity coefficients

arma: Estimate ARMA model coefficients using maximum likelihood

autofit: Find the best model from a range of possible ARMA models

burg: Estimate AR coefficients using the Burg method

check: Check for causality and invertibility

deaths: USA accidental deaths, 1973 to 1978

dowj: Dow Jones utilities index, August 28 to December 18, 1972

forecast: Forecast future values

hannan: Estimate ARMA coefficients using the Hannan-Rissanen...

hr: Estimate harmonic components

ia: Estimate MA coefficients using the innovations algorithm

itsmr-package: Time series analysis package for students

lake: Level of Lake Huron, 1875 to 1972

ma.inf: Compute MA infinity coefficients

periodogram: Plot a periodogram

plota: Plot data and/or model ACF and PACF

plotc: Plot one or two time series

plots: Plot spectrum of data or ARMA model

Resid: Compute residuals

season: Estimate seasonal component

selftest: Run a self test

sim: Generate synthetic observations

smooth.exp: Apply an exponential filter

smooth.fft: Apply a low pass filter Apply a moving average filter

smooth.rank: Apply a spectral filter

specify: Specify an ARMA model

strikes: USA union strikes, 1951-1980

Sunspots: Number of sunspots, 1770 to 1869

test: Test residuals for stationarity and randomness

trend: Estimate trend component

wine: Australian red wine sales, January 1980 to October 1991

yw: Estimate AR coefficients using the Yule-Walker method

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