Using GoldSim's built-in probabilistic simulation capabilities, it is straightforward to perform statistical analysis of time series data. This model uses Monte Carlo simulation to analyze monthly time series data of a rate to produce monthly and annual flow statistics. In addition to this, the model calculates probability distributions for each month and compares it to an analytical distribution then finds a best fit probability distribution for all months. It is assumed that the flow units are in cubic feet per second (cfs).
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I tried to use this model with my own data. For some reason, some of the months have some kind of horizontal shift between empirical and analytical curves. What could be causing this?
Atlin,
Thank you for bringing this to my attention. I found a bug in the way we gather the monthly analytical and empirical values within the Analytical submodel. Please download the attached updated model, which I've uploaded to this article and try running it again with your data. I tried this with your time series and get the following result:
In case you are curious, this change was made to the 2 script elements inside the "Analytical" submodel. I now reference the month counter ~M so that we assign the samples for the correct month instead of referencing the entire array:
If you still have the model that you ran with my data, could you send it to me please? I tried to input my time series into the updated model on this page, but I may have made an error trying to adapt the model from daily to monthly data, as I'm still getting an error during February.
Would you mind sending the input time series to me? That way, I can verify correct functionality before sending you the model. I might find another issue that is causing your February anomalies. Please start a new support ticket and attach a zip file. Thank you so much! Below is the link: https://support.goldsim.com/hc/en-us/requests/new
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