TSUNIMAR Call
determines the order of an AR process with the minimum
AIC procedure and estimates the AR coefficients
- CALL TSUNIMAR( arcoef, ev, nar, aic, data
- <,maxlag, opt, missing,
print>);
The inputs to the TSUNIMAR subroutine are as follows:
- data
- specifies a (or ) data
vector, where is the number of observations.
- maxlag
- specifies the maximum lag of the AR process.
This value should be less than half the number of
observations.
The default is maxlag=10.
- opt
- specifies an options vector.
- opt[1]
- specifies the mean deletion option.
The mean of the original data is deleted if opt[1]=-1.
An intercept term is estimated if opt[1]=1.
If opt[1]=0, the original input data are processed
assuming that the mean value of the input data is 0.
The default is opt[1]=0.
- opt[2]
- specifies the minimum AIC option.
If opt[2]=0, the maximum lag
AR process is estimated.
The minimum AIC option, opt[2]=1, is the default.
- missing
- specifies the missing value option.
By default, only the first contiguous observations
with no missing values are used (missing=0).
The missing=1 option ignores
observations with missing values.
If you specify the missing=2 option, the
missing values are replaced with the sample mean.
- print
- specifies the print option.
By default, printed output is suppressed (print=0).
The print=1 option prints the final estimation result, while
the print=2 option prints intermediate and final results.
The TSUNIMAR subroutine returns the following values.
- arcoef
- refers to an AR
coefficient vector if the intercept is not included.
If opt[1]=1, the first element of the
arcoef vector is an intercept estimate.
- ev
- refers to the error variance.
- nar
- refers to the selected AR order by minimum AIC procedure.
If opt[2]=0, nar = maximum lag.
- aic
- refers to the minimum AIC value.
The TSUNIMAR subroutine determines the order of the AR process by
using the minimum AIC procedure and estimates the AR coefficients.
All AR coefficient estimates up to maximum lag
are printed if you specify the print option.
See the section
"Least Squares and Householder Transformation" for more information.
Copyright © 2009 by SAS Institute Inc., Cary, NC, USA. All rights reserved.