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Keywords:
time series
There are many MacAnova functions that are useful in time series
analysis. In addition there are two files, tser.mac and arima.mac,
containing macros for doing frequency domain and time domain analyses.
Functions useful in time series analysis
Fast Fourier transforms (FFT) for Complex, Hermitian, and Real series
cft(), hft(), rft()
Functions for working with complex and Hermitian series and Fourier
transforms
cconj(), creal(), cimag(), cpolar(), crect(), cprdc(), cprdcj(),
hconj(), hreal(), himag(), hpolar(), hrect(), hprdh(), hprdhj(),
cmplx(), ctoh(), htoc(), unwind(), reverse(), padto(), rotate()
Autoregressive and moving average operators and their zeros
autoreg(), movavg(), polyroot()
Other functions
convolve(), partacf(), yulewalker()
Type, for example, 'usage(cft)' or 'help(cft)', to get a thumbnail
sketch or a complete description of cft().
Macros for time series analysis
File tser.mac, distributed with MacAnova, contains the following macros:
arspectrum Estimate spectrum of autoregression by solving the Yule-
Walker equations
autocor Compute autocorrelation function
autocov Compute autocovariance function
burg Estimate autoregression coefficients using Burg's
algorithm and optionally compute the spectrum of the
fitted moddel
compfa Compute smoothed modified periodograms and, optionally,
cross periodograms, using cosine tapering, with optional
detrending
compza Compute the Fourier transform of a cosine tapered
series, optionally detrending
costaper Compute a cosine taper with a specified amount of
tapering
crsspectrum Compute smoothed periodgrams and cross periodogram with
no tapering or detrending
detrend Remove a polynomial trend in equally spaced time
dpss Compute discrete prolate spheroidal sequences
evalpoly Evaluate a real polynomial of a complex variable
ffplot Plot a frequency function against frequency
gettsmacros Retrieves macros from tser.mac
multitaper Compute multitaper spectrum estimates
spectrum Compute smoothed periodograms with no tapering or
detrending
testnfreq Test whether its argument has prime factors > 29
tsplot Plot time series against time
These can be retrieved by, for example, getmacros(multitaper) or
multitaper <- macroread("tser.mac","multitaper").
Help for these macros is available in file tser.hlp. You can get help
on these macros using help(). If you know a macro is in tser.mac, it
may be faster to use pre-defined macro tserhelp(). For example, to get
help on burg(), type tserhelp(burg). See topic tserhelp() for details.
tserhelp() also can retrieve the following informational topics from
tser.hlp:
bandwidth Comments about the bandwidth and EDF of spectrum
estimates
complex_data Information on representing complex data and series in
MacAnova
complex_fun Summary of MacAnova functions for working with complex
series
fourier Information concerning Fourier transforms
hermitian Information on complex series with Hermitian symmetry
See help() for information on direct use of help() to retrieve help
information from tser.hlp and arima.mac.
File arima.mac, distributed with MacAnova, contains the following
macros:
acfarma Compute autocovariance function of ARMA model
arima Fit ARIMA model or linear regression with ARIMA errors
by unconditional least squares or MLE estimation
arimares Compute residuals from ARIMA model; used by macros
arima, hannriss, innovest.
hannriss Fit an ARIMA model using the Hannan-Rissannen algorithm
innovations Compute the coefficients for one step prediction in
terms of previous one-step prediction errors. Used by
macro innovest
innovest Fit an ARIMA model using the innovations algorithm
levmar Fit a non-linear model by least squares using a form of
the Levenberg-Marquart algorithm
moveoutroots Fix up coefficients for a MA or AR operator so that all
the zeros are outside the unit circle in the complex
plane
nlreg Fit a non-linear regression model by least squares.
rhatcovar Compute variances and or covariances of sample
autocorrelations or the entire variance matrix of the
sample autocorrelation function using Bartlett's formula
rhatvar Compute variances of sample auto correlations using
Bartlett's formula
specarma Compute spectrum of ARMA model
File arima.mac serves as its own help file from which the help topics
can be retrived either by help() or by pre-defined macro arimahelp().
If you know a topic is in arima.mac, arimahelp() may be faster since it
searches only one file. To get help on, say, macro arima(), type
arimahelp(arima) or help(arima). See arimahelp() for details.
See help() for information on direct use of help() to retrieve help
information from tser.hlp and arima.mac.
See also topics 'macros', macroread(), getmacros(), usage(),
macrousage().
Gary Oehlert
2003-01-15