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<html>
<head>
<title>
STARPAC - Statistical Data Analysis Library
</title>
</head>
<body bgcolor="#EEEEEE" link="#CC0000" alink="#FF3300" vlink="#000055">
<h1 align = "center">
STARPAC <br> Statistical Data Analysis Library
</h1>
<hr>
<p>
<b>STARPAC</b>
is a FORTRAN90 library which
contains a number of routines for statistical data analysis.
</p>
<p>
<b>STARPAC</b> uses a COMMON block and EQUIVALENCE statements
in order to make workspace storage available to its routines.
This scheme assumes that an integer is stored in one word.
When compiling this program with <b>G95</b>, it may be necessary
to include the <b>-i4</b> switch, to guarantee that integers
are stored in 4 bytes = one word. Otherwise, routines that
rely on the workspace storage system will fail.
</p>
<h3 align = "center">
Languages:
</h3>
<p>
<b>STARPAC</b> is available in
<a href = "../../f77_src/starpac/starpac.html">a FORTRAN77 version</a> and
<a href = "../../f_src/starpac/starpac.html">a FORTRAN90 version</a>.
</p>
<h3 align = "center">
Related Data and Programs:
</h3>
<p>
<a href = "../../f_src/blas1/blas1.html">
BLAS1</a>,
a FORTRAN90 library which
implements the
Basic Linear Algebra Subprograms, Level 1, and which are
called by <b>STARPAC</b>.
</p>
<p>
<a href = "../../f_src/machine/machine.html">
MACHINE</a>,
a FORTRAN90 library which
tabulates the values
of certain machine-specific arithmetic quantities, and which are
called by <b>STARPAC</b>.
</p>
<p>
<a href = "../../f_src/nl2sol/nl2sol.html">
NL2SOL</a>,
a FORTRAN90 library which
minimizes the
sum of squares of a set of nonlinear functions, and which is
called by <b>STARPAC</b>.
</p>
<p>
<a href = "../../f_src/prob/prob.html">
PROB</a>,
a FORTRAN90 library which
computes the PDF, CDF, inverse CDF, and sampling various statistical
distributions.
</p>
<p>
<a href = "../../f_src/uniform/uniform.html">
UNIFORM</a>,
a FORTRAN90 library which
carries out uniform sampling of real, complex or integer data.
</p>
<p>
<a href = "../../f_src/xerror/xerror.html">
XERROR</a>,
a FORTRAN90 library which
carries out error handling.
</p>
<h3 align = "center">
Reference:
</h3>
<p>
<ol>
<li>
Milton Abramowitz, Irene Stegun,<br>
Handbook of Mathematical Functions,<br>
National Bureau of Standards, 1964,<br>
LC: QA47.A34,<br>
ISBN: 0-486-61272-4.
</li>
<li>
Peter Bloomfield,<br>
Fourier Analysis of Time Series - An Introduction,<br>
Wiley, 2000,<br>
ISBN: 0471889482,<br>
LC: QA280.B59.
</li>
<li>
Nancy Bosten, Thomas Aird,<br>
Remark on Algorithm 179, <br>
Communications of the ACM,<br>
Volume 17, page 153, 1974.
</li>
<li>
George Box, Gwilym Jenkins,<br>
Time Series Analysis: Forecasting and Control,<br>
Prentice Hall, 1991,<br>
ISBN: 0139051007,<br>
LC: QA280.B67.
</li>
<li>
Kenneth Brown,<br>
A Quadratically Convergent Newton-like Method Based upon
Gaussian Elimination,<br>
SIAM Journal on Numerical Analysis,<br>
Volume 6, pages 560-569, 1969.
</li>
<li>
Peter Businger, Gene Golub,<br>
Linear Least Squares Solutions by Householder Transformations,<br>
Numerische Mathematik,<br>
Volume 7, pages 269-276, 1965.
</li>
<li>
Alan Cline, Cleve Moler, Pete Stewart, James Wilkinson,<br>
An Estimate of the Condition Number of a Matrix,<br>
Technical Report TM-310,<br>
Applied Math Division,<br>
Argonne National Laboratory, 1977.
</li>
<li>
John Dennis, David Gay, Roy Welsch,<br>
Algorithm 573:
An Adaptive Nonlinear Least-Squares Algorithm,<br>
ACM Transactions on Mathematical Software,<br>
Volume 7, Number 3, 1981, pages 367-383.
</li>
<li>
Janet Donaldson, Peter Tryon,<br>
User's Guide to STARPAC,<br>
The Standards Time Series and Regression Package,<br>
NIST, Boulder, Colorado, 1987.
</li>
<li>
Jack Dongarra, Jim Bunch, Cleve Moler, Pete Stewart,<br>
LINPACK User's Guide,<br>
SIAM, 1979,<br>
ISBN13: 978-0-898711-72-1,<br>
LC: QA214.L56.
</li>
<li>
Norman Draper, Harry Smith,<br>
Applied Regression Analysis,<br>
Wiley, 1998,<br>
ISBN: 978-0471170822,<br>
LC: QA278.2.D7.
</li>
<li>
Merran Evans, Nicholas Hastings, Brian Peacock,<br>
Statistical Distributions,<br>
Wiley, 2000,<br>
ISBN: 0471371246,<br>
LC: QA273.6E92.
</li>
<li>
Enrico Federghi,<br>
Extended Tables of the Percentage Points of Student's
T-Distribution,<br>
Journal of the American Statistical Association,<br>
Volume 54, Number 287, 1959, pages 683-688.
</li>
<li>
Phyllis Fox, Andrew Hall, Norman Schryer,<br>
Algorithm 528,
A Framework for a Portable Library,<br>
ACM Transactions on Mathematical Software,<br>
Volume 4, Number 2, June 1978, pages 177-188.
</li>
<li>
Walter Gautschi,<br>
Algorithm 542:
Incomplete Gamma Functions,<br>
ACM Transactions on Mathematical Software,<br>
Volume 5, Number 4, December 1979, pages 382-489.
</li>
<li>
David Gay,<br>
Computing Optimal Locally Constrained Steps,<br>
SIAM Journal on Scientific and Statistical Computing,<br>
Volume 2, Number 2, pages 186-197, 1981.
</li>
<li>
Philip Gill, Walter Murray,<br>
Algorithms for the Solution of the
Non-linear Least-squares Problem, <br>
SIAM Journal on Numerical Analysis,<br>
Volume 15, Number 5, pages 977-991, 1978.
</li>
<li>
Steven Goldfeld, Richard Quandt, Hale Trotter,<br>
Maximization by Quadratic Hill-climbing,<br>
Econometrica,<br>
Volume 34, pages 541-551, 1966.
</li>
<li>
MD Hebden,<br>
An Algorithm for Minimization using Exact Second Derivatives,<br>
Report TP515,<br>
Theoretical Physics Division,<br>
AERE, Harwell, Oxon., England, 1973.
</li>
<li>
DC Hoaglin,<br>
Theoretical Properties of Congruential Random-Number Generators,
An Empirical View,<br>
Memorandum NS-340,<br>
Department of Statistics,<br>
Harvard University, 1976.
</li>
<li>
Gwilym Jenkins, Donald Watts,<br>
Spectral Analysis and its Applications,<br>
Holden-Day, 1968,<br>
ISBN: 1892803038,<br>
LC: QA280.J45.
</li>
<li>
Norman Johnson, Samuel Kotz, Narayanaswamy Balakrishnan,<br>
Continuous Univariate Distributions,<br>
Second edition,<br>
Wiley, 1994,<br>
ISBN: 0471584940,<br>
LC: QA273.6.J6
</li>
<li>
Donald Knuth,<br>
The Art of Computer Programming,<br>
Volume 2, Seminumerical Algorithms,<br>
Third Edition,<br>
Addison Wesley, 1997,<br>
ISBN: 0201896842,<br>
LC: QA76.6.K64.
</li>
<li>
Charles Lawson, Richard Hanson,<br>
Solving Least Squares Problems,<br>
SIAM, 1995,<br>
ISBN: 0898713560,<br>
LC: QA275.L38.
</li>
<li>
Charles Lawson, Richard Hanson, David Kincaid, Fred Krogh,<br>
Algorithm 539:
Basic Linear Algebra Subprograms for Fortran Usage,<br>
ACM Transactions on Mathematical Software,<br>
Volume 5, Number 3, September 1979, pages 308-323.
</li>
<li>
George Marsaglia, Wai Wan Tsang,<br>
A fast, easily implemented method for sampling from decreasing or
symmetric unimodal density functions,<br>
SIAM Journal of Scientific and Statistical Computing,<br>
Volume 5, 1983, pages 349-359.
</li>
<li>
Jorge More,<br>
The Levenberg-Marquardt Algorithm, Implementation and Theory,<br>
in Springer Lecture Notes in Mathematics, Number 630,<br>
edited by G A Watson,<br>
Springer, 1978.
</li>
<li>
Donald Owen, <br>
Handbook of Statistical Tables,<br>
Addison-Wesley, 1962.
</li>
<li>
Egon Pearson, Herman Hartley, <br>
Biometrika Tables for Statisticians, <br>
Cambridge, 1970,<br>
ISBN: 978-0852647004.
</li>
<li>
Michael Powell,<br>
A Fortran Subroutine for Solving Systems of Nonlinear
Algebraic Equations,<br>
in Numerical Methods for Nonlinear Algebraic Equations,<br>
edited by Philip Rabinowitz,<br>
Gordon and Breach, 1970,<br>
ISBN13: 978-0677142302,<br>
LC: QA218.N85.
</li>
<li>
CS Smith,<br>
Multiplicative Pseudo-Random Number Generators with Prime Modulus,<br>
Journal of the Association for Computing Machinery,<br>
Volume 19, pages 586-593, 1971.
</li>
<li>
Richard Varga,<br>
Minimal Gerschgorin Sets,<br>
Pacific Journal of Mathematics,<br>
Volume 15, pages 719-729, 1965.
</li>
<li>
Max Waldmeier,<br>
The Sunspot-Activity in the Years 1610-1960,<br>
Shulthess, 1961,<br>
LC: QB525.W34.
</li>
<li>
Martin Wilk, Ram Gnanadesikan, Marilyn Huyett,<br>
Probability Plots for the Gamma Distribution,<br>
Technometrics,<br>
Volume 4, Number 1, 1962, pages 1-15,
</li>
</ol>
</p>
<h3 align = "center">
Source Code:
</h3>
<p>
<ul>
<li>
<a href = "starpac.f90">starpac.f90</a>,
the source code.
</li>
<li>
<a href = "starpac.csh">starpac.csh</a>,
commands to compile the source code.
</li>
</ul>
</p>
<h3 align = "center">
Examples and Tests:
</h3>
<p>
<ul>
<li>
<a href = "starpac_prb.f90">starpac_prb.f90</a>,
a sample calling program.
</li>
<li>
<a href = "starpac_prb.csh">starpac_prb.csh</a>,
commands to compile, link and run the sample calling program.
</li>
<li>
<a href = "starpac_prb_output.txt">starpac_prb_output.txt</a>,
the output from a run of the sample calling program.
</li>
</ul>
</p>
<h3 align = "center">
List of Routines:
</h3>
<p>
<ul>
<li>
<b>ABSCOM</b> counts the entries of | V(1:N) - W(1:N) | greater than ABSTOL.
</li>
<li>
<b>ACCDIG</b> returns the number of accurate digits in an approximation to X.
</li>
<li>
<b>ACFD</b> computes autocorrelations and partial autocorrelations.
</li>
<li>
<b>ACFDTL</b> prints titles for ACORRD.
</li>
<li>
<b>ACFER</b> does error checking for the ACF routines.
</li>
<li>
<b>ACF</b> is the simple interface to the autocorrelations routines.
</li>
<li>
<b>ACFF</b> computes autocorrelations of a time series using an FFT.
</li>
<li>
<b>ACFFS</b> uses an FFT with ACVF estimates for autocorrelations of a time series.
</li>
<li>
<b>ACFLST</b> lists the autocorrelations and other information.
</li>
<li>
<b>ACFM</b> computes autocorrelations of a time series with missing data.
</li>
<li>
<b>ACFMN</b> computes autocorrelations of a time series.
</li>
<li>
<b>ACFMNF</b> computes autocorrelations of a time series.
</li>
<li>
<b>ACFMNM</b> computes autocorrelations of a time series with missing data.
</li>
<li>
<b>ACFMS</b> is the user interface for autocorrelations of a time series with missing data.
</li>
<li>
<b>ACFOUT</b> prints autocorrelations.
</li>
<li>
<b>ACFSD</b> computes the standard error of autocorrelations.
</li>
<li>
<b>ACFSDM</b> computes the standard error of autocorrelations with missing data.
</li>
<li>
<b>ACFS</b> computes autocorrelations with computed ACVF estimates.
</li>
<li>
<b>ACVF</b> computes the autocovariance function of a series.
</li>
<li>
<b>ACVFF</b> computes the ACVF of a series using two FFT passes.
</li>
<li>
<b>ACVFM</b> computes autocovariance when missing data is involved.
</li>
<li>
<b>ADJLMT</b> corrects the plot limits when all observations are equal.
</li>
<li>
<b>AIMEC</b> is the user interface for ARIMA estimation.
</li>
<li>
<b>AIME</b> is the user interface for ARIMA estimation, control call.
</li>
<li>
<b>AIMES</b> is the user interface for ARIMA estimation, long call.
</li>
<li>
<b>AIMF</b> is the user interface for ARIMA estimation, short call.
</li>
<li>
<b>AIMFS</b> is the user interface for ARIMA estimation, control call.
</li>
<li>
<b>AIMX1</b> sets the starting parameter values for AIMX.
</li>
<li>
<b>ALBETA</b> computes the logarithm of the Beta function.
</li>
<li>
<b>ALGAMS</b> evaluates the log of the absolute value of the Gamma function.
</li>
<li>
<b>ALNGAM</b> computes the logarithm of the absolute value of the Gamma function.
</li>
<li>
<b>ALNREL</b> evaluates log ( 1 + X ) with relative error control.
</li>
<li>
<b>AMDRV</b> estimates the jacobian matrix.
</li>
<li>
<b>AMEAN</b> computes the arithmetic mean of a series.
</li>
<li>
<b>AMEANM</b> computes the arithmetic mean of a series with missing data.
</li>
<li>
<b>AMECNT</b> is the control routine for nonlinear least squares regression.
</li>
<li>
<b>AMEDRV</b> is the control routine for nonlinear least squares regression.
</li>
<li>
<b>AMEER</b> checks errors for the nonlinear least squares estimation.
</li>
<li>
<b>AMEFIN</b> analyzes nonlinear least squares estimates after they are computed.
</li>
<li>
<b>AMEHDR</b> prints headings for nonlinear least squares estimation.
</li>
<li>
<b>AMEISM</b> prints an initial summary for nonlinear least squares routines.
</li>
<li>
<b>AMEMN</b> is the control routine for using the NL2 software package.
</li>
<li>
<b>AMEOUT</b> prints the final summary output from ARIMA estimation.
</li>
<li>
<b>AMEPT1</b> prints data summary for nonlinear least squares routines.
</li>
<li>
<b>AMEPT2</b> prints four standardized residual plots.
</li>
<li>
<b>AMESTP</b> controls the step size selection.
</li>
<li>
<b>AMFCNT</b> is the control routine for ARIMA forecasting.
</li>
<li>
<b>AMFER</b> checks errors for nonlinear least squares estimation.
</li>
<li>
<b>AMFHDR</b> prints headers for nonlinear least squares estimation.
</li>
<li>
<b>AMFMN</b> computes and prints ARIMA forecasts.
</li>
<li>
<b>AMFOUT</b> produces ARIMA forecasting output.
</li>
<li>
<b>AMLST1</b> prints parameters for the ARIMA routine.
</li>
<li>
<b>AMLST</b> prints parameter summaries from ARIMA forecasting.
</li>
<li>
<b>AOS</b> computes autoregressive model order selection statistics.
</li>
<li>
<b>AOSLST</b> lists the autoregressive model order selection statistics.
</li>
<li>
<b>AOV1ER</b> does preliminary checks on input to the one-way family.
</li>
<li>
<b>AOV1</b> is a user interface to AOV1MN, one-way analysis of variance.
</li>
<li>
<b>AOV1HD</b> prints headers for the one-way ANOVA family.
</li>
<li>
<b>AOV1MN</b> computes results for analysis of a one-way classification.
</li>
<li>
<b>AOV1S</b> is a user interface for AOV1MN, one-way analysis of variance.
</li>
<li>
<b>AOV1XP</b> prints storage for one-way family exerciser.
</li>
<li>
<b>ARCOEF</b> uses Durbin's method for autoregression coefficients with order lag.
</li>
<li>
<b>ARFLT</b> performs autoregressive filtering.
</li>
<li>
<b>ASSESS</b> assesses a candidate step.
</li>
<li>
<b>AXPBY:</b> SZ(1:N) = SA * SX(1:N) + SB * SY(1:N).
</li>
<li>
<b>BACKOP</b> computes the number of back order terms for an ARIMA model.
</li>
<li>
<b>BETAI</b> computes the incomplete Beta ratio.
</li>
<li>
<b>BFSDRV</b> is the driver for time series Fourier spectrum analysis.
</li>
<li>
<b>BFSER</b> checks errors for time series Fourier univariate spectrum analysis.
</li>
<li>
<b>BFS:</b> short interface for time series Fourier bivariate spectrum analysis.
</li>
<li>
<b>BFSF:</b> short interface for time series Fourier bivariate spectrum analysis.
</li>
<li>
<b>BFSFS:</b> long interface for time series Fourier bivariate spectrum analysis.
</li>
<li>
<b>BFSLAG:</b> lag window truncation points for Fourier bivariate spectral analysis.
</li>
<li>
<b>BFSM:</b> short interface for time series bivariate Fourier spectrum analysis.
</li>
<li>
<b>BFSMN</b> computes square coherency and phase components of a bivariate spectrum.
</li>
<li>
<b>BFSMS:</b> long interface for BFS analysis with missing observations.
</li>
<li>
<b>BFSMV:</b> short interface for BFS analysis, missing observations, covariances.
</li>
<li>
<b>BFSMVS:</b> long interface for BFS analysis, missing observations, covariances.
</li>
<li>
<b>BFSS:</b> long call for time series bivariate Fourier spectrum analysis.
</li>
<li>
<b>BFSV:</b> short call for BFS analysis, with covariance input rather than series.
</li>
<li>
<b>BFSVS:</b> long call for BFS analsys with covariances input rather than series.
</li>
<li>
<b>CCFER</b> does error checking for CCF routines.
</li>
<li>
<b>CCF</b> computes the cross-correlation of two time series.
</li>
<li>
<b>CCFF</b> computes the cross-correlation of two time series by Singleton's FFT.
</li>
<li>
<b>CCFFS</b> computes multivariate cross-correlations and covariances by FFT.
</li>
<li>
<b>CCFLST</b> lists cross-correlations, standard errors, and summary information.
</li>
<li>
<b>CCFM</b> computes cross-correlation of two series with missing data.
</li>
<li>
<b>CCFMN</b> is the main routine for cross-correlations.
</li>
<li>
<b>CCFMNF</b> is the main routine for cross-correlations using an FFT.
</li>
<li>
<b>CCFMNM</b> is the main routine for cross-correlations with missing data.
</li>
<li>
<b>CCFMS</b> is a user routine for multivariate cross-correlations.
</li>
<li>
<b>CCFOUT</b> prints cross-correlations and standard errors.
</li>
<li>
<b>CCFSD</b> is the main routine for computing standard error of cross-correlations.
</li>
<li>
<b>CCFSDM:</b> standard error of cross-correlations with missing data.
</li>
<li>
<b>CCFS</b> is the user routine for multivariate cross-correlations.
</li>
<li>
<b>CCFXP</b> lists results for the time series cross-correlation routines.
</li>
<li>
<b>CCVF</b> computes the cross covariance function between two series.
</li>
<li>
<b>CCVFF</b> computes the cross covariance function between two series.
</li>
<li>
<b>CCVFM</b> computes the cross covariance function of two series with missing data.
</li>
<li>
<b>CDFCHI</b> computes the CDF for the Chi Square distribution.
</li>
<li>
<b>CDFF</b> computes the CDF for the F distribution.
</li>
<li>
<b>CDFNML</b> computes the CDF for the standard normal distribution.
</li>
<li>
<b>CDFT</b> computes the CDF for Student's T distribution.
</li>
<li>
<b>CENTER</b> centers an observed series.
</li>
<li>
<b>CHIRHO</b> computes the Chi Square statistic and its probability.
</li>
<li>
<b>CMPFD</b> computes a finite difference derivative.
</li>
<li>
<b>CNTR</b> centers the input seriers about its mean.
</li>
<li>
<b>CORRER</b> checks for errors in the input parameters.
</li>
<li>
<b>CORR:</b> short call to correlation family of routines.
</li>
<li>
<b>CORRHD</b> prints headers for the correlation family.
</li>
<li>
<b>CORRMN</b> is the main routine in the correlation family.
</li>
<li>
<b>CORRS</b> is the user routine for the correlation, with a long call interface.
</li>
<li>
<b>CORRXP</b> prints stored output returned from CORRS.
</li>
<li>
<b>COVCLC</b> computes the covariance matrix for NL2ITR.
</li>
<li>
<b>CPYASF</b> copies a symmetric matrix stored rowwise into rectangular storage.
</li>
<li>
<b>CPYMSS</b> copies an N by M matrix.
</li>
<li>
<b>CPYVII</b> copies an integer vector.
</li>
<li>
<b>CSEVL</b> evaluates a Chebyshev series.
</li>
<li>
<b>D1MACH</b> returns double precision machine constants.
</li>
<li>
<b>DCKCNT</b> controls the derivative checking process.
</li>
<li>
<b>DCKCRV</b> checks whether high curvature caused poor derivative approximation.
</li>
<li>
<b>DCKDRV</b> is the driver to the derivative checking routines.
</li>
<li>
<b>DCKER</b> does error checking for the derivative checking routines.
</li>
<li>
<b>DCKFPA</b> checks if arithmetic precision causes poor derivative approximation.
</li>
<li>
<b>DCKHDR</b> prints page headers for the derivative checking routines.
</li>
<li>
<b>DCKLS1</b> sets up a problem for testing the step size selection family.
</li>
<li>
<b>DCKLSC</b> is the user routine for comparing analytic and numeric derivatives.
</li>
<li>
<b>DCKLS</b> is the user routine for comparing analytic and numeric derivatives.
</li>
<li>
<b>DCKMN</b> is the main routine for checking analytic versus numeric derivatives.
</li>
<li>
<b>DCKOUT</b> prints results from the derivative checking routine.
</li>
<li>
<b>DCKZRO</b> rechecks derivative errors where the analytic derivative is zero.
</li>
<li>
<b>DCOEF</b> expands a difference filter.
</li>
<li>
<b>DEMDRV</b> is the driver routine to demodulate a series.
</li>
<li>
<b>DEMOD</b> demodulates a series at a given frequency.
</li>
<li>
<b>DEMODS</b> demodulates a series at a given frequency.
</li>
<li>
<b>DEMODU</b> demodulates a series at a given frequency.
</li>
<li>
<b>DEMORD</b> sets up the data for the phase plots.
</li>
<li>
<b>DEMOUT</b> prints output for the time series demodulation routines.
</li>
<li>
<b>DFAULT</b> supplies default values to IV and V.
</li>
<li>
<b>DFBW</b> computes degrees of freedom and bandwidth for a given lag window.
</li>
<li>
<b>DFBWM</b> computes DOF and BW for a given lag window with missing data.
</li>
<li>
<b>DIFC</b> expands a difference filter and performs difference filtering.
</li>
<li>
<b>DIF</b> performs a first difference filtering operation.
</li>
<li>
<b>DIFMC</b> expands a difference filter and performs the difference filter.
</li>
<li>
<b>DIFM</b> performs a first difference filter for a series with missing data.
</li>
<li>
<b>DIFSER</b> performs a differencing operation on a series.
</li>
<li>
<b>DOTC</b> computes the dot product of two series, centered about their means.
</li>
<li>
<b>DOTCM</b> computes the dot product of series with missing data.
</li>
<li>
<b>DOTPRD</b> returns the inner product of two vectors.
</li>
<li>
<b>DRV1A</b> derivative function for NLS family exerciser subroutine MDL1.
</li>
<li>
<b>DRV1B</b> is an INCORRECT derivative function for the NLS exerciser MDL1.
</li>
<li>
<b>DRV2</b> is a derivative function for the NLS exerciser routine MD12.
</li>
<li>
<b>DRV3</b> is the derivative function for NLS family exerciser subroutine MDL3.
</li>
<li>
<b>DRV4A</b> is a (correct) derivative for testing derivative checking routines.
</li>
<li>
<b>DRV4B</b> is an (incorrect) derivative for testing derivative checking routines.
</li>
<li>
<b>DRV</b> is a dummy derivative function for the NLS family.
</li>
<li>
<b>DUPDAT</b> updates the scale vector for NL2ITR.
</li>
<li>
<b>E9RINT</b> stores the current error message or prints the old one.
</li>
<li>
<b>ECVF</b> prints an error message if missing data affects the covariance lags.
</li>
<li>
<b>EHDR</b> prints the heading for the error checking routines.
</li>
<li>
<b>EIAGE</b> ensures that "not too many" vectors are below a given lower bound.
</li>
<li>
<b>EIAGEP</b> prints the error messages for ERAGT and ERAGTM.
</li>
<li>
<b>EISEQ</b> prints an error message if NVAL is not equal to NEQ.
</li>
<li>
<b>EISGE</b> prints a warning if NVAL is less than NMIN.
</li>
<li>
<b>EISII</b> warns if an integer value does not lie within a given range.
</li>
<li>
<b>EISLE</b> warns if an integer is greater than a given maximum.
</li>
<li>
<b>EISRNG</b> warns if ISEED is not a suitable random number seed.
</li>
<li>
<b>EIVEO</b> checks whether all vector entries are even (or odd).
</li>
<li>
<b>EIVEQ</b> warns if the vector does not have at least NEQMN entries equal to IVAL.
</li>
<li>
<b>EIVII</b> warns if too many values are outside given limits.
</li>
<li>
<b>ENFFT</b> checks that NFFT is suitable for the Singleton FFT routine.
</li>
<li>
<b>EPRINT</b> prints the last error message, if any.
</li>
<li>
<b>ERAGT</b> warns if too many values are less than a lower bound.
</li>
<li>
<b>ERAGTM</b> warns if too many values are less than or equal to a lower bound.
</li>
<li>
<b>ERAGTP</b> prints the error messages for ERAGT and ERAGTM.
</li>
<li>
<b>ERDF</b> checks the values that specify differencing on a time series.
</li>
<li>
<b>ERFC</b> evaluates the complementary error function.
</li>
<li>
<b>ERF</b> evaluates the error function.
</li>
<li>
<b>ERIODD</b> warns if the value of NVAL is inconsistent.
</li>
<li>
<b>ERSEI</b> warns if a value is not between given limits.
</li>
<li>
<b>ERSGE</b> warns if a value is not greater than or equal to a minimum value.
</li>
<li>
<b>ERSGT</b> warns if the input value is not greater than a specified minumum.
</li>
<li>
<b>ERSIE</b> warns if a value is not within a specified range.
</li>
<li>
<b>ERSII</b> warns if the input value is not within the given range.
</li>
<li>
<b>ERSLF</b> checks the definition of a symmetric linear filter.
</li>
<li>
<b>ERSLFS</b> checks values specifying a symmetric linear filter for a time series.
</li>
<li>
<b>ERVGT</b> ensures that "most" values are greater than a specified lower bound.
</li>
<li>
<b>ERVGTM</b> ensures that "most" values are greater than a specified lower bound.
</li>
<li>
<b>ERVGTP</b> prints the error messages for ERVGT and ERVGTM.
</li>
<li>
<b>ERVII</b> checks for vector values outside given limits.
</li>
<li>
<b>ERVWT</b> checks user-supplied weights.
</li>
<li>
<b>ETAMDL</b> computes noise and number of good digits in model routine results.
</li>
<li>
<b>EXTEND</b> returns the I-th term in a series.
</li>
<li>
<b>FACTOR</b> factors an integer.
</li>
<li>
<b>FDUMP</b> is a dummy version of the dump routine called by XERRWV.
</li>
<li>
<b>FFTCT</b> does a cosine transform of n=2*n2 symmetric data points.
</li>
<li>
<b>FFT</b> is a multivariate complex Fourier transform.
</li>
<li>
<b>FFTLEN</b> computes the value of NFFT for the Singleton FFT routine.
</li>
<li>
<b>FFTR</b> is the user-callable routine for the Fourier transform of a series.
</li>
<li>
<b>FITEXT</b> checks whether the fit is exact to machine precision.
</li>
<li>
<b>FITPT1</b> prints the data summary for nonlinear least squares routines.
</li>
<li>
<b>FITPT2</b> prints the four standardized residual plots.
</li>
<li>
<b>FITSXP</b> generates reporst for least squares exerciser returned storage.
</li>
<li>
<b>FITXSP</b> generates reports for least squares exerciser returned storage.
</li>
<li>
<b>FIXPRT</b> sets the character array 'FIXED'.
</li>
<li>
<b>FLTAR</b> filters an input series using an autoregressive filter.
</li>
<li>