I have applied the update to the documentation (although that function
needs a general rewrite - later...)
>On Mon, Aug 15, 2011 at 8:53 AM, Andrea Gavana wrote:
>
>> Hi Chris and All,
>>
>> On 12 August 2011 16:53, Christopher Jordan-Squire wrote:
>> > Hi Andrea--An easy way to get something like
On Mon, Aug 15, 2011 at 8:53 AM, Andrea Gavana wrote:
> Hi Chris and All,
>
> On 12 August 2011 16:53, Christopher Jordan-Squire wrote:
> > Hi Andrea--An easy way to get something like this would be
> >
> > import numpy as np
> > import scipy.stats as stats
> >
> > sigma = #some reasonable standar
Hi Chris and All,
On 12 August 2011 16:53, Christopher Jordan-Squire wrote:
> Hi Andrea--An easy way to get something like this would be
>
> import numpy as np
> import scipy.stats as stats
>
> sigma = #some reasonable standard deviation for your application
> x = stats.norm.rvs(size=1000, loc=125
Hi Chris & Brennan,
On 15 August 2011 00:59, Brennan Williams wrote:
> You can use scipy.stats.truncnorm, can't you? Unless I misread, you want to
> sample a normal distribution but with generated values only being within a
> specified range? However you also say you want to do this with triangula
You can use scipy.stats.truncnorm, can't you? Unless I misread, you want
to sample a normal distribution but with generated values only being
within a specified range? However you also say you want to do this with
triangular and log normal and for these I presume the easiest way is to
sample an
Hi Andrea--An easy way to get something like this would be
import numpy as np
import scipy.stats as stats
sigma = #some reasonable standard deviation for your application
x = stats.norm.rvs(size=1000, loc=125, scale=sigma)
x = x[x>50]
x = x[x<200]
That will give a roughly normal distribution to
Hi All,
I am working on something that appeared to be a no-brainer issue (at the
beginning), by my complete ignorance in statistics is overwhelming and I got
stuck.
What I am trying to do can be summarized as follows
Let's assume that I have to generate a sample of a 1,000 values for a
varia
