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I am developing an app for time series analysis that should support the following:

Are you familiar with open source stat packages other than R, that supports these models? (Python?)

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  • $\begingroup$ Add features that test the normality of the errors which would include 1) Intervention Detection to disclose Pulses/Level Shifts/Seasonal Pulses 2) non-constant variance of the errors due to changes in parameters over time or due to break-points in variance suggesting the need for power transformations and/or Garch .You should also be looking for automatic detection of lead and lag structureSs (PDL) around user-specified causal/regressor series.Additionally being able to sort out the need for ARIMA versus fixed predictors e.g.day-of-the-week would along with optimal ARIMA structure. $\endgroup$
    – IrishStat
    Mar 24, 2012 at 19:58
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    $\begingroup$ R is really going to be your best bet here for open source. $\endgroup$
    – Zach
    Sep 26, 2012 at 16:06
  • $\begingroup$ @lilile Yes AUTOBOX . Available from Automatic Forecasting Systems .They have 30 day demo available at autobox.com/30day.exe . $\endgroup$
    – IrishStat
    Sep 26, 2012 at 19:03
  • $\begingroup$ @lililie I should have mentioned I am one of the developers of this program. $\endgroup$
    – IrishStat
    Sep 26, 2012 at 20:10

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pmdarima gives you (S)ARIMA models, with orders chosen by minimizing AIC. You don't want to do the Box-Jenkins approach, information criteria are superior. statsmodels gives you multiple regression, which in turn can fit curves. I don't know of a module that does exponential smoothing, Croston's method or Bass models.

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