Wind speed forecasting using ARIMA model

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I have the readings of wind speed and I want to forecast it for the next year. However, when I use autocorrelation and Partial autocorrelation I realise that the data must be differenced for once. I have also tried to use ARIMA(2,1,1) - based on autocorr and parcorr - but the forecasted results are different from the actual ones. Can anyone help me on how to accurately identify the order of AR() and MA() so the forecasting can be as much accurate as possible?

Accepted Answer

Shashank Prasanna
Shashank Prasanna on 11 Jul 2014
Forecast will never be identical to the actual series. After all this is a model. To quote famous statistician George Box "essentially, all models are wrong, but some are useful". Unfortunately there isn't a magic way to select lag orders, however there are several strategies you can use to improve results. For a start take a look at a surveys common strategies for lag order selection here:
Other examples that use autocorrelation and paritial autocorrelation along with aic and bic:

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