Hi, @ Warren: I was thinking of using federico method as its quite simple. I know the mu and sigma of log(values) and I need to plot a normal distribution based on that. Anything inaccurate in doing that?
@ Sebastian: Thanks for your suggestion. I got to know more about powerlaw distributions. But, I dont think my values have a long tail. do you think it is still relevant? What are the potential applications of the same? Thanks & Regards, Sanant On Thu, May 26, 2016 at 7:50 PM, Sebastian Benthall <[email protected]> wrote: > You may also be interested in the 'powerlaw' Python package, which detects > the tail cutoff. > On May 26, 2016 5:46 AM, "Warren Weckesser" <[email protected]> > wrote: > >> >> >> On Thu, May 26, 2016 at 2:08 AM, Startup Hire <[email protected]> >> wrote: >> >>> Hi all, >>> >>> Hope you are doing good. >>> >>> I am working on a project where I need to do the following things: >>> >>> 1. I need to fit a lognormal distribution to a set of values [I know its >>> lognormal by a simple XY scatter plot in excel] >>> >>> >> >> The probability distributions in scipy have a fit() method, and >> scipy.stats.lognorm implements the log-normal distribution ( >> http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.lognorm.html) >> so you can use scipy.lognorm.fit(). See, for example, >> http://stackoverflow.com/questions/26406056/a-lognormal-distribution-in-python >> or http://stackoverflow.com/ >> /questions/15630647/fitting-lognormal-distribution-using-scipy-vs-matlab >> >> Warren >> >> >> >>> 2. I need to find the intersection of the lognormal distribution so that >>> I can decide cut-off values based on that. >>> >>> >>> Can you guide me on (1) and (2) can be achieved in python? >>> >>> Regards, >>> Sanant >>> >>> _______________________________________________ >>> scikit-learn mailing list >>> [email protected] >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >>> >> >> _______________________________________________ >> scikit-learn mailing list >> [email protected] >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > >
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