Big thx, it is good way,
Intresting is also this

dagr = diff(a) ./ diff(gradient(x))

and another offset avg ...

Paul

W dniu wtorek, 27 maja 2014 17:37:41 UTC+2 użytkownik Tomas Lycken napisał:
>
> If you have the y-values in a sorted vector, and the x-values in another 
> sorted vector (or if they're just the index you don't need them), you can 
> get the discrete derivative by using diff:
>
> da = diff(a) ./ diff(x)
>
> Now, the tangential tilt is less than 45 degrees whenever that derivative 
> is larger than -1, so 
>
> a[da .< -1]
>
> will give you the portion of a for which the slope is steeper than 45 
> degrees. (I might be off by one here, so you might want to experiment a 
> little and see if you need to include one more, or one less, data point to 
> get exactly what you want...)
>
> // T
>
> On Tuesday, May 27, 2014 4:53:52 PM UTC+2, paul analyst wrote:
>>
>> Thanks for the cool link. 
>> Generally this is the point where the tangential tilt is 45 degrees.
>> Paul
>>
>> W dniu wtorek, 27 maja 2014 15:06:25 UTC+2 użytkownik Harlan Harris 
>> napisał:
>>>
>>> Paul, I don't believe that this is a well-posed question. Determining 
>>> what is the tail of a distribution and what isn't is very much 
>>> problem-dependent. "getting flat" depends entirely on the scale of your 
>>> data, and isn't meaningful. You could do what people constructing boxplots 
>>> do, and use some multiple of the inter-quartile range from the median, but 
>>> that still depends on the source, distribution, and meaning of your data. 
>>> In any case, you'd be better off asking this somewhere like CrossValidated (
>>> http://stats.stackexchange.com/) -- this isn't a Julia question.
>>>
>>>
>>> On Tue, May 27, 2014 at 8:22 AM, paul analyst <[email protected]>wrote:
>>>
>>>> Does not work always, distributions are different.
>>>> How to find the number of elements of the vector from which the chart is 
>>>> getting flat (where is the beginning of the tail?)
>>>> Paul
>>>>
>>>>
>>>> W dniu wtorek, 27 maja 2014 12:19:09 UTC+2 użytkownik Yuuki Soho 
>>>> napisał:
>>>>
>>>>> The simplest way to do it is probably to use a quantile:
>>>>>
>>>>>
>>>>> a=[5 3 2 1.5 1.1 1 0.8 0.25 0.2 0.16]
>>>>>
>>>>> q = quantile(vec(a),0.1)
>>>>>
>>>>> a = a[1:cut] 
>>>>>
>>>>>
>>>>>
>>>

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