[Home] . . . Search by [Problem] [Package] [Module] [Keyword] . . . [Math at NIST]

GAMS Module ACFF in STARPAC


ACFF

 
Compute and print a two-part auto- and partial correlation analysis of a series,
select the order of an autoregressive process which models the series, and
estimate the parameters of this model; use FFT for computations.
 
Classes  :  L10a2a .  Time series summary statistics
            L10a2c1 . Autoregressive model identification
 
Type     : Fortran subroutine in STARPAC library.
Access   : Public domain. Portable.
Precision: Single.
 
Usage    : CALL ACFF (YFFT, N, LYFFT, LDSTAK)
 
Details  : Documentation Fullsource Source
Sites    : (1) ARNO (2) ITL
 

Implementation of ACFF from STARPAC on ARNO

 
ARNO:      Silicon Graphics Origin 2000, National Institute of Standards and
           Technology (NIST), Gaithersburg, MD. Available to NIST staff.
 
Precision: Single.
 
Those logged in to arno.nist.gov or amur.nist.gov may access this module as
follows.
 
   Link         : See starpac man page.
   Documentation: Help Packages starpac Doc-By-Subprogram ACFF
   Source       : Help Packages starpac source ACFF
   Example      : Help Packages starpac examples
 

Implementation of ACFF from STARPAC on ITL

 
ITL:       Unix Workstation Network, National Institute of Standards and
           Technology (NIST), Gaithersburg, MD. Available to NIST staff.
 
Precision: Single.
 
Access available only to NIST staff on internal Unix systems. They may access this
package provided the /itl tree is cross-mounted.
 
   Link         : f77 myprog myprog.f -lstarpac
   Documentation: help Package starpac Doc-By-Subprogram ACFF
   Source       : help packages starpac source ACFF
   Fullsource   : starsrcx acff


[Home] . . . Search by [Problem] [Package] [Module] [Keyword] . . . [Math at NIST]

GAMS is a service of the Mathematical and Computational Sciences Division of the Information Technology Laboratory of the National Institute of Standards and Technology

This page was generated on Sat Sep 20, 2008 at 03:22:55 UTC