TSPEARS Call
analyzes periodic AR models with the minimum AIC procedure
- CALL TSPEARS( arcoef, ev, nar, aic, data
- <,maxlag, opt, missing,
print>);
The inputs to the TSPEARS subroutine are as follows:
- data
- specifies a T ×1 (or 1 ×T) data matrix.
- maxlag
- specifies the maximum lag of the periodic AR process.
This value should be less than [1/2J] of the input series.
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 coefficient is estimated if opt[1]=1.
If opt[1]=0, the original input data is processed
assuming that the mean values of input series are zeroes.
The default is opt[1]=0.
- opt[2]
- specifies the number of instants per period.
By default, opt[2]=1.
- opt[3]
- specifies the minimum AIC option.
If opt[3]=0, the maximum lag
AR process is estimated.
If opt[3]=1, the minimum AIC procedure is used.
The default is opt[3]=1.
- 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 periodic
AR estimates and intermediate process.
The TSPEARS subroutine returns the following values:
- arcoef
- refers to a periodic AR coefficient
matrix of the periodic AR model.
If opt[1]=1, the first column of the
arcoef matrix is an intercept estimate vector.
- ev
- refers to the error variance.
- nar
- refers to the selected AR order vector of the periodic AR model.
- aic
- refers to the minimum AIC values of the periodic AR model.
The TSPEARS subroutine analyzes the periodic
AR model by using the minimum AIC procedure.
The data of length T are divided into d periods.
There are J instants in one period.
See the "Multivariate Time Series Analysis" section for details.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
