[scikit-learn] Fitting Lognormal Distribution

[federico vaggi]

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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