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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
  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
  compza        Compute the Fourier transform of a cosine tapered
                series, optionally detrending
  costaper      Compute a cosine taper with a specified amount of
  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
  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

  bandwidth     Comments about the bandwidth and EDF of spectrum
  complex_data  Information on representing complex data and series in
  complex_fun   Summary of MacAnova functions for working with complex
  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
  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
  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(),

Gary Oehlert 2003-01-15