This topic contains 3 replies, has 2 voices, and was last updated by Ryu 2 months, 4 weeks ago.
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Home 2015 › Forums › Numerical Method › Statistics › About SuanShu API
This topic contains 3 replies, has 2 voices, and was last updated by Ryu 2 months, 4 weeks ago.
I wanna forecast a value by fitting an ARIMA model based on a time series of historical records. I’ve used the trial SuanShu 3.4.0 API. With this trial API, could I train ARMA model parameters and predict the next term value? Does the offical version of SuanShu provide some simple examples or user manual about ARIMA mode. I am new with Suanshu and any advise or help will be appreciated. Thank you.
The full version of SS has classes to estimate ARMA models. Please see these examples.
But the free version does not allow using the statistical API. You may request a full one month trial license by emailing info [a t] nm [d o t] sg
Thank you for your response.
In ARMA modeling, the first step is to identify the model (i.e., the values of p for AR and q for MA) by looking at plots of the ACF and PACF. Is it possible to realize this step by SuanShu API (without figuring out these two plots)?
Here is what we/SuanShu suggests:
1.
Determine the lags (p and q) of the ARMA process and fit an ARMA(p, q) model. This is done by the usual ARMA fitting procedure., e.g., ConditionalSumOfSquares
2.
Select a suitable set of orders (P, Q) for the GARCH process. We can do this by looking at the PACF and ACF of the squared residuals and possibly use Ljung-Box test.
3.
Fit a pure GARCH(P, Q) model to the residuals using conditional MLE.
4.
Diagnostic checks.
You can do all steps 1 – 4 in SuanShu by calling the appropriate classes.
See this for more information:
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