MATLAB: Forecasting with an AR(8) model

Econometrics Toolboxforecastingforecasting with ar model

Hi, I am totally newly in Matlab and I have a question.

I have a time series and I want to apply an AR(8) model to forecast the next 12 observations.

I dont think that I could understand/follow the Mathworks instructions.

Any help??

Thank you!

Best Answer

Have you seen the doc already? If you haven't here's the link to ARIMA models:

http://www.mathworks.com/help/econ/arima.estimate.html

You can estimate your AR coefficients from data and then use the model to forecast. Give it a try and if you have specific question let us know.

Related Solutions

MATLAB: One step ahead forecast from an estimated model – error term

1. The arima\estimate method will return to you the data on the original scale. That is if you do:

Mdl = arima(1,1,1);
Mdl = estimate(Mdl,data);
res = infer(Mdl,data); % Retrieve inferred residuals (innovations)
foreValues = forecast(Mdl,1,'Y0',data','E0',res) % forecast

Your forecasted data will be on the same scale as data and not the differenced data. The difference operator is just applied and you have the model you wrote above, but are simply returned y(k),y(k+1),...

2. The residual e(k-1) is he last value in the variable res above. That is, if you pass 'E0' to the forecast method it will use the residuals which were infered from the model and data.

MATLAB: Autoregressive models

Example: AR(1)

% Generate series

Series = rand(100,1);

% Set the AR(1) - note the constant variance

Spec = garchset('R',1,'VarianceModel','Constant');

% Estimate

[Coeff,Errors,LLF]  = garchfit(Spec,Series);

% Display

garchdisp(Coeff,Errors)
aicbic(LLF,garchcount(Coeff))

Alternatively:

Econometrics Toolbox: by James P. LeSage (free): function ar
MFE_Toolbox (free): function armaxfilter

Best Answer

Related Solutions

MATLAB: One step ahead forecast from an estimated model – error term

MATLAB: Autoregressive models

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