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So here's the problem:

I am dealing with about 200 time-series of banking accounts that have drawn on a credit at some point. I know the point when they got the credit (let's call this point t(credit) ) and know the account balance from t(0) - t(credit)

Now I want to build a model which tells me, how high the chance for taking a credit is for other accounts that have not taken one so far.

In other words: I want to know at which point a customer takes on a credit.

I know that this is not realy a multiple time series, since the series don't effect each other.

The closest slution so far is described in this article which is not totaly reproducable to me in some parts.

My questions:

  1. What kind of statistical test/ machine learning algorithm can solve the problem?

  2. Is there an R-Package that might help me?

I hope the problem is described clearly enough... sorry for bad english

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Dan Jel Schneider
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  • Please read [(1)](https://stackoverflow.com/help/how-to-ask) how do I ask a good question, [(2)](https://stackoverflow.com/help/mcve) how to create a MCVE as well as [(3)](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example#answer-5963610) how to provide a minimal reproducible example in R. Then edit and improve your question accordingly. I.e., abstract from your real problem... – Christoph May 28 '18 at 13:22
  • Your English is not bad to me; but one specific question at a time would drive more people to help you. – vahdet May 28 '18 at 13:33
  • Hi Dan, stackoverflow is for specific programming questions ie you know what analysis you want to do, how to do it but are struggling with some specific part of the programming of it. For more statistical advice on methods, you could try asking at https://stats.stackexchange.com/ or https://datascience.stackexchange.com/ – user20650 May 28 '18 at 13:48
  • Thx for the ansers, I've s et up a new question with a data example https://stackoverflow.com/questions/50580908/prediction-of-unlikely-events-with-multiple-time-series-r – Dan Jel Schneider May 29 '18 at 09:30

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