Err, sorry - mu1, mu2, sigma1, sigma2, where mu1, sigma1 are the mean/standard deviation of the first distribution, and mu2, sigma2 are the mean and standard deviation of the second distribution.
On Thu, 26 May 2016 at 09:26 federico vaggi <[email protected]> wrote: > If you are talking about finding the values at which the probability > density functions will have the same value, then you can just write the > equations explicitly and solve in terms of theta1, sigma1 and theta2, > sigma2? > > > On Thu, 26 May 2016 at 09:23 Startup Hire <[email protected]> > wrote: > >> 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 >>> >>> >> _______________________________________________ >> scikit-learn mailing list >> [email protected] >> https://mail.python.org/mailman/listinfo/scikit-learn >> >
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