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src/c/o/cogent-1.5.3/cogent/maths/stats/distribution.py   cogent(Download)
"""
from __future__ import division
from cogent.maths.stats.special import erf, erfc, igamc, igam, betai, log1p, \
    expm1, SQRTH, MACHEP, MAXNUM, PI, ndtri, incbi, igami, fix_rounding_error,\
    ln_binomial
    if df < 1:
        raise ValueError, "chi_low: df must be >= 1 (got %s)." % df
    return igam(df/2, x/2)
 
def chi_high(x, df):
    if m < 0:
        raise ValueError, "Poisson m must be >= 0."
    return igam(k+1, m)
 
def fdtr(a, b, x):
    if x < 0.0:
        raise ZeroDivisionError, "x must be at least 0."
    return igam( b, a * x)
 
def gdtrc(a, b, x):

src/p/y/pycogent-HEAD/cogent/maths/stats/distribution.py   pycogent(Download)
"""
from __future__ import division
from cogent.maths.stats.special import erf, erfc, igamc, igam, betai, log1p, \
    expm1, SQRTH, MACHEP, MAXNUM, PI, ndtri, incbi, igami, fix_rounding_error,\
    ln_binomial
    if df < 1:
        raise ValueError, "chi_low: df must be >= 1 (got %s)." % df
    return igam(df/2, x/2)
 
def chi_high(x, df):
    if m < 0:
        raise ValueError, "Poisson m must be >= 0."
    return igam(k+1, m)
 
def fdtr(a, b, x):
    if x < 0.0:
        raise ZeroDivisionError, "x must be at least 0."
    return igam( b, a * x)
 
def gdtrc(a, b, x):

src/c/o/cogent-1.5.3/cogent/maths/stats/period.py   cogent(Download)
    factorial = lambda x: Gamma(x+1)
 
from cogent.maths.stats.special import igam
 
__author__ = "Hua Ying, Julien Epps and Gavin Huttley"
    s = ((numpy.ones((N-p,), float)-sim)**2).sum()
    D = s/(N-p)
    p_val = 1 - igam(df/2.0, D/2)
    return D, p_val
 

src/p/y/pycogent-HEAD/cogent/maths/stats/period.py   pycogent(Download)
    factorial = lambda x: Gamma(x+1)
 
from cogent.maths.stats.special import igam
 
__author__ = "Hua Ying, Julien Epps and Gavin Huttley"
    s = ((numpy.ones((N-p,), float)-sim)**2).sum()
    D = s/(N-p)
    p_val = 1 - igam(df/2.0, D/2)
    return D, p_val