1) The normal distribution is parametrized by standard deviation and mean. Simply take the mean and standard deviation of the log of your values?
2) Which curves? You only mentioned a single log normal distribution. On Thu, 26 May 2016 at 08:42 Startup Hire <[email protected]> wrote: > Hi Michael, > > :) > > > (1) - I think you are right, how do I fit a normal distribution to the > log of values? > > (2) Intersection ---> Meeting point (s) . as in where the curves cross > each other (it can be in multiple places too!) > > > Regards, > Sanant > > On Thu, May 26, 2016 at 11:52 AM, Michael Eickenberg < > [email protected]> wrote: > >> Hi Sanant, >> >> On Thursday, May 26, 2016, Startup Hire <[email protected]> wrote: >> >>> Hi all, >>> >>> Hope you are doing good. >>> >> >> I would like to think so, but you never know where ML will lead us ... >> >> >>> >>> 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] >>> >> >> if your distribution is lognormal, why don't you try fitting a gaussian >> to the log of the values? is this too unstable? >> >> >>> >>> 2. I need to find the intersection of the lognormal distribution so that >>> I can decide cut-off values based on that. >>> >> >> what exactly do you mean by intersection? >> >> >>> >>> >>> Can you guide me on (1) and (2) can be achieved in python? >>> >>> Regards, >>> Sanant >>> >> >> >> Michael >> >> _______________________________________________ >> 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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