[scikit-learn] Fitting Lognormal Distribution

[federico vaggi]

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
>>>>>
>>>>> _______________________________________________
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>>>>>
>>>>>
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