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Mathematica Data Analysis by Sergiy Suchok

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Choosing the best time series process model

As we have become acquainted with the main processes, now we can proceed with their forecasts. To do this, let's get to know the TimeSeriesModelFit function by considering the following example. Suppose we have data on the air temperature in London from January 1, 2012 to September 1, 2015, and we want to get the forecast for the next 6 days. Moreover, we want to compare how the forecast we receive will differ from the actual one. We will also build 95% confidence intervals that should include almost all the possible results of the forecast:

Choosing the best time series process model

Take into account that Mathematica has reported that the SARIMA ...

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