ARMA forecasting

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Marina
Marina 2012-4-16
评论： Abolfazl Nejatian 2020-12-10
Hello all. I have a time series, and I have to apply the four steps of ARMA estimation ( chose the orders, compute the coefficients of the suitable ARMA model), and after that I have to predict the next 10 values. I am a beginer in this domain, and I have insatlled the Matlab 2010b. Thank you for your Help
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hamed Aghapanah
hamed Aghapanah 2019-10-5
Dear,
Can it forcasting a stochastic signal?
Abolfazl Nejatian
Abolfazl Nejatian 2020-12-10
this is my forcasting code which is allow you predict your time series data with LSTM, CNN, and MLP Networks.
https://www.mathworks.com/matlabcentral/fileexchange/69506-time-series-prediction

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Rajiv Singh
Rajiv Singh 2012-4-16
Use ARMAX function in System Identification Toolbox to estimate an ARMA model, as in model = arma(data, [na nc])
In R2012a: use FORECAST function to forecast the response. See http://www.mathworks.com/help/toolbox/ident/ref/forecast.html
Previous releases: See http://www.mathworks.com/matlabcentral/answers/12186-forecasting-function
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Marina
Marina 2012-4-17
thank you. but my question is how to chose the ordes na and nc? (I think I have to calculate ACF and PACF) and after that how to calculate my coeficients
Rajiv Singh
Rajiv Singh 2012-4-17
System identification toolbox has no automated way for you to pick na/nc. The ARXSTRUCT/SELSTRUC commands let you for this for a ARX model structure. You could subject your data to this command and determine "na" that way. Then you can pick nc<=na as a start. The "optimal" values of na and nc orders are ultimately going to be those for which the prediction errors are minimized against a validation data set.
See COMPARE and RESID commands. The most basic test of optimality would be that the 1-step ahead prediction fit to validation data is maximized, as revealed in the COMPARE plot.

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