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I´ve 838 sets of data that represents points distributed by height. Those that can be fitted by Weibull function. So, I normalized them and adjusted the corresponding distribution function, saving it´s coefficients using scipy.exponweib (loc, scale).

I'd like to use this data to stratify those 838 set´s of data, grouping it in similar height profile.

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closed as unclear what you're asking by Michael Chernick, Sycorax, Jeremy Miles, kjetil b halvorsen, Ferdi Nov 20 '18 at 11:36

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

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    $\begingroup$ Possible; sure; you might potentially do some form of clustering in parameter space. You might even be able take the parameter variances and covariances into account (for example, estimates from large samples will tend to be more precisely estimated than from small samples). Whether it makes sense to do so is less clear. Perhaps there's a better way to approach what you're attempting. What are you trying to achieve by doing so? $\endgroup$ – Glen_b Nov 19 '18 at 23:23
  • $\begingroup$ I´m trying to stratify those data by the Weibull dist characteristics. After that, I intend to compare the strata information with another data I have about the data in a way to determine if Weibull distribution "explains" these other data. $\endgroup$ – Mauro Assis Nov 22 '18 at 16:53