>>> (in code lines below leaving out the python console prompt ">>>") dataset=scipy.stats.pareto.rvs(1.5,size=10000) #generating data scipy.stats.pareto.fit(dataset) however this results in (1.0, nan, 0.0) (exponent 1, should be 1.5) and. It's more general than the Pareto distribution.One might call it a generalized Pareto distribution but I wouldn't because that term also means something else.Can we standardize on Wikipedia usage of these names, please? The generalized Pareto distribution has three basic forms, each corresponding to a limiting distribution of exceedance data from a different class of underlying distributions. Distributions whose tails decrease exponentially, such as the normal, lead to a generalized Pareto shape parameter of zero. Assuming that when you say Generalized Pareto you mean the two-parameter version such as the one discussed in (McNeil 1997) and not the three parameter version as brought in (Klugman et. \$ python Python 3.3.0 (default, Dec 12 2012, 07:43:02) [GCC 4.7.2] on linux Type "help", "copyright", "credits" or "license" for more information. Notes. Parameters : -> q : lower and upper tail probability-> a, b : shape parameters-> x : quantiles-> loc : [optional]location parameter. al. It is also known as the “80-20 rule”. Pareto is very popular diagarm in Excel and Tableu. I have already estimated the threshold that I will consider, created the pdf of the extreme values that I will take into account and currently trying to fit to this a Generalized Pareto Distribution. Default = 0-> scale : [optional]scale parameter. A generalized Pareto continuous random variable. The distribution you describe is usually called Beta prime distribution, and is implemented as betaprime in SciPy. Lomax can also be considered as a simplified version of the Generalized Pareto distribution (available in SciPy), with the scale set to one and the location set to zero. The Generalized Pareto distribution (GP) was developed as a distribution that can model tails of a wide variety of distributions, based on theoretical arguments. In excel we can easily draw a Pareto diagram but I found no easy way to draw the diagram in Python. As an instance of the rv_continuous class, genpareto object inherits from it a collection of generic methods (see below for the full list), and completes them with details specific for this particular distribution. The Pareto distribution must be greater than zero, and is unbounded above. 1998)—also known as the Beta of the second kind—you can use the pot for R which provides among its fitting functions the function fitgpd which will fit a GPD. scipy.stats.genpareto() is an generalized Pareto continuous random variable that is defined with a standard format and some shape parameters to complete its specification.