In article <[EMAIL PROTECTED]>, [EMAIL PROTECTED] says... > [EMAIL PROTECTED] wrote: > > I was wondering if scipy/numpy has the inverse cumulative normal > > function, ie the function f in this expression > > > > f(scipy.stats.norm.cdf(1.2)) = 1.2 > > > > or more generally, a function f which fits the criteria > > > > f(scipy.stats.norm.cdf(x)) = x > > Look in the file where all of the distributions are defined, > Lib/stats/distributions.py . You will find that each distribution object also > has a method call .ppf(), the Percent Point Function, the inverse of the CDF. > > In [1]: from scipy.stats import norm > > In [2]: norm.ppf(norm.cdf(1.2)) > Out[2]: array(1.2000000000000004) > > > There is a distribution called invnorm, but I am not sure of how to use > > it. > > invnorm is another probability distribution entirely. Don't bother with it. > > Great thanks very much. Exactly what I was looking for. And seeing the scipy.info for ppf, that's exactly what it says as well. Got distracted by the invnorm distribution :-( -- http://mail.python.org/mailman/listinfo/python-list
