Input a Time Series and Fit ARMA Model

<< FitARMA.m

Normally one would input the data using the built-in function ReadList or the FitAR function ReadData.  For convience, the data is already loaded in the notebook.

seriesa = {17. , 16.6, 16.3, 16.1, 17.1, 16.9, 16.8, 17.4, 17.1, 
          17. , 16.7, 17.4, 17.2, 17.4, 17.4, 17. , 17.3, 17.2, 17.4, 16.8, 
          17.1, 17.4, 17.4, 17.5, 17.4, 17.6, 17.4, 17.3, 17. , 17.8, 17.5, 
          18.1, 17.5, 17.4, 17.4, 17.1, 17.6, 17.7, 17.4, 17.8, 17.6, 17.5, 
          16.5, 17.8, 17.3, 17.3, 17.1, 17.4, 16.9, 17.3, 17.6, 16.9, 16.7, 
          16.8, 16.8, 17.2, 16.8, 17.6, 17.2, 16.6, 17.1, 16.9, 16.6, 18. , 
          17.2, 17.3, 17. , 16.9, 17.3, 16.8, 17.3, 17.4, 17.7, 16.8, 16.9, 
          17. , 16.9, 17. , 16.6, 16.7, 16.8, 16.7, 16.4, 16.5, 16.4, 16.6, 
          16.5, 16.7, 16.4, 16.4, 16.2, 16.4, 16.3, 16.4, 17. , 16.9, 17.1, 
          17.1, 16.7, 16.9, 16.5, 17.2, 16.4, 17. , 17. , 16.7, 16.2, 16.6, 
          16.9, 16.5, 16.6, 16.6, 17. , 17.1, 17.1, 16.7, 16.8, 16.3, 16.6, 
          16.8, 16.9, 17.1, 16.8, 17. , 17.2, 17.3, 17.2, 17.3, 17.2, 17.2, 
          17.5, 16.9, 16.9, 16.9, 17. , 16.5, 16.7, 16.8, 16.7, 16.7, 16.6, 
          16.5, 17. , 16.7, 16.7, 16.9, 17.4, 17.1, 17. , 16.8, 17.2, 17.2, 
          17.4, 17.2, 16.9, 16.8, 17. , 17.4, 17.2, 17.2, 17.1, 17.1, 17.1, 
          17.4, 17.2, 16.9, 16.9, 17. , 16.7, 16.9, 17.3, 17.8, 17.8, 17.6, 
          17.5, 17. , 16.9, 17.1, 17.2, 17.4, 17.5, 17.9, 17. , 17. , 17. , 
          17.2, 17.3, 17.4, 17.4, 17. , 18. , 18.2, 17.6, 17.8, 17.7, 17.2, 
          17.4};

List of All Functions and Variables Used

?FitARMA`*

Using FitARMA

This function also computes residuals as well as the parameter standard errors.

?FitARMA

Options[FitARMA]

FitARMA[seriesa,  {1, 0, 1}]

Using GetARMAFit

This is more terse.  This function was used in the Timing experiments.

?GetARMAFit

It is assumed that the mean is zero.  So, it is very important that the input series is mean corrected for this function.  If the original nonzero mean data is used, an error message may result.

y = seriesa - Mean[seriesa];

GetARMAFit[1, 1, 30, y]

Using HRARMA

HRARMA[1, 1, seriesa]

It is not assumed that the mean is zero.

Using GetARMAMeanFit

?GetARMAMeanFit

With this function the mean is assumed to be nonzero so we can use the original data.

GetARMAMeanFit[1, 1, 30, seriesa]