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POHow to predict when next event occurs based on previous events?
 

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  1. POHow to predict when next event occurs based on previous events?
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    <p>Basically, I have a reasonably large list (a year's worth of data) of times that a single discrete event occurred (for my current project, a list of times that someone printed something). Based on this list, I would like to construct a statistical model of some sort that will predict the most likely time for the next event (the next print job) given all of the previous event times.</p> <p>I've already read <a href="https://stackoverflow.com/questions/758036/predict-next-event-occurrence-based-on-past-occurrences">this</a>, but the responses don't exactly help out with what I have in mind for my project. I did some additional research and found that a <a href="http://en.wikipedia.org/wiki/Hidden_Markov_model" rel="nofollow noreferrer">Hidden Markov Model</a> would likely allow me to do so accurately, but I can't find a link on how to generate a Hidden Markov Model using just a list of times. I also found that using a <a href="http://en.wikipedia.org/wiki/Kalman_filter" rel="nofollow noreferrer">Kalman filter</a> on the list may be useful but basically, I'd like to get some more information about it from someone who's actually used them and knows their limitations and requirements before just trying something and hoping it works.</p> <p>Thanks a bunch!</p> <p><strong>EDIT</strong>: So by Amit's suggestion in the comments, I also posted this to the <a href="https://stats.stackexchange.com/questions/16302/how-to-predict-when-the-next-event-occurs-based-on-times-of-previous-events">Statistics StackExchange, CrossValidated</a>. If you do know what I should do, please post either here or there</p>
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    1. COMaybe you could generate a list of 0s and 1s, putting ones where the events occur, zeros otherwise, then train a neural net to recognize the pattern. Basically if your list is 1000 events long, and you want to predict the next 100, then use a 1000->100 neural net.
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    2. COYou will probably get better answers in [statistics stackexchange](http://stats.stackexchange.com/)
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    3. CODidn't know about that! I guess I should just repost this over there?
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