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How can I check if my data fits a Pareto distribution?
Here is a link to a histogram of my data.. And I wish to check if my data fits a Pareto distribution, but I don’t want to see QQ plots with that distribution, but I need an exact answer with p-value in R, such as Anderson-Darling test for normality ( ad.test ). How could I do that? Please be as specific as you can.
How to calculate the KS of a Pareto distribution?
First define the basic functions to deal with Pareto distributions. The following function computes the MLE of the parameters (justifications in Wikipedia ). And this functions compute the KS statistic, and uses parametric bootstrap to estimate the p -value.
Is the Pareto approximation good for real data?
Please be as specific as you can. (PS) First of all I think Glen_b is right in his above comments on the usefulness of such a test: real data are surely not exactly Pareto distributed, and for most practical applications the question would be “how good is the Pareto approximation?”
Which is the best way to test for a distribution?
The first method that almost everyone knows is the histogram. The histogram is a data visualization that shows the distribution of a variable. It gives us the frequency of occurrence per value in the dataset, which is what distributions are about. The histogram is a great way to quickly visualize the distribution of a single variable.
How to fit data to Burr distribution in R?
How do I fit a set of data to Burr Distribution in R? For example I have a data set as: (2042.044,2218.153,3670.893,5149.684,5533.429,7111.183,11041.569,15459.771,783.477,1701.520,40810.770,67905.857) How do I fit the above data in Burr distribution to compute its parameters in R? fitdist does not provide Burr distribution.
Do you know how to parameterize Pareto-IV to become Burr?
So if you know how to parameterize Pareto-IV to become Burr, you can use their dparetoIV function to for fitdstr, and their rparetoIV if you want to simulate data. Thanks for contributing an answer to Cross Validated! Please be sure to answer the question.