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If I have some data regarding the occurence of an event on a certain date and some other variables regarding it (think fe.: I have data on which dates it rained, and some addtitional data like temperature, atmospheric pressure etc.), which is the most appropriate model for predicting on which day the event is going to happen again? Or, to be more precise, I'd like to predict the frequency of said event, to know in how many days it's going to occur again. I mostly use Python with the numpy, sklearn libraries, and I'm interested which of its models fits my use case best.

Thank you!

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  • $\begingroup$ have you been able to do the prediction using which models? Thanks $\endgroup$ Aug 18, 2017 at 10:24
  • $\begingroup$ This was for a hobby project, which I abandoned, so I didn't even have time to try anything, sorry... $\endgroup$
    – lte__
    Aug 21, 2017 at 8:15

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You should read that :

http://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/

and take a look at that :

http://statsmodels.sourceforge.net/0.6.0/generated/statsmodels.tsa.arima_model.ARIMA.html

The endog argument is your time serie and the exog is your other data

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