[scikit-learn] Fitting Lognormal Distribution

Startup Hire blrstartuphire at gmail.com
Thu May 26 05:58:57 EDT 2016


Thanks

On Thu, May 26, 2016 at 12:57 PM, federico vaggi <vaggi.federico at gmail.com>
wrote:

> 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 <vaggi.federico at gmail.com>
> 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 <blrstartuphire at gmail.com>
>> 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 <
>>> vaggi.federico at gmail.com> 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 <blrstartuphire at gmail.com>
>>>> 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 <
>>>>> michael.eickenberg at gmail.com> wrote:
>>>>>
>>>>>> Hi Sanant,
>>>>>>
>>>>>> On Thursday, May 26, 2016, Startup Hire <blrstartuphire at gmail.com>
>>>>>> 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
>>>>>> scikit-learn at python.org
>>>>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>>>>
>>>>>>
>>>>> _______________________________________________
>>>>> scikit-learn mailing list
>>>>> scikit-learn at python.org
>>>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>>>
>>>>
>>>> _______________________________________________
>>>> scikit-learn mailing list
>>>> scikit-learn at python.org
>>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>>
>>>>
>>> _______________________________________________
>>> scikit-learn mailing list
>>> scikit-learn at python.org
>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>
>>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20160526/10cafc11/attachment.html>


More information about the scikit-learn mailing list