Hi, (1) - Thanks. will do that
(2) - I am fitting the distribution for 2 different set of values.. I will find the distribution as mentioned by you in (1).. But, now having 2 curves, how do i find the meetings point(s) ? Regards, Sanant On Thu, May 26, 2016 at 12:16 PM, federico vaggi <[email protected]> wrote: > 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 >> > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > >
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