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# cogent.maths.stats.special.igam

All Samples(12)  |  Call(8)  |  Derive(0)  |  Import(4)

```"""
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):
```

```"""
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):
```

```    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

```

```    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

```