Description of the program: ar-model

This program fits (by means of least squares) a simple autoregressive (AR) model to the possibly multivariate data. The model is given by the equation
The matrices Ai are determined by the program.
The output file contains the coefficients of the model and the residuals. Note that now the mean is subtracted first, conforming with common practice. If you want to run the resulting model to generate a time series, you can either use the -s flag of the program or pipe the output to ar-run. Note that no attempt has been made to generate a stable model.


ar-model [Options]

Everything not being a valid option will be interpreted as a potential datafile name. Given no datafile at all, means read stdin. Also - means stdin

Possible options are:

Option Description Default
-l# number of data to use whole file
-x# number of lines to be ignored 0
-m# dimension of the vectors 1
-c# column to be read 1,...,dimension of the vectors
-p# order of the model 5
-s# iterate s steps of the model no iteration
-o# output file name without file name: 'datafile'.ar
(or if stdin was used)
if no -o is given stdout is used
-V# verbosity level
  0: only panic messages
  1: add input/output messages
  2: print residuals though iterating a model
-h show these options none

Description of the Output:

The first line just contains the average forecast errors of the model for each component of the vector x, the next p*(dimension of the vectors) lines contain the AR coefficients for each of the components. The rest of the file are the individual errors (residuals) or a iterated time series depending on the flag -s.
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