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# cogent.maths.stats.special.igamc

All Samples(8)  |  Call(6)  |  Derive(0)  |  Import(2)

```"""
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_high: df must be >= 1 (got %s)." % df
return igamc(df/2, x/2)

def t_low(t, df):
```
```    if m < 0:
raise ValueError, "Poisson m must be >= 0."
return igamc(k+1, m)

def pdtrc(k, m):
```
```    if x < 0.0:
raise ZeroDivisionError, "x must be at least 0."
return igamc(b, a * x)

#note: ndtri for the normal distribution is already imported
```

```"""
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_high: df must be >= 1 (got %s)." % df
return igamc(df/2, x/2)

def t_low(t, df):
```
```    if m < 0:
raise ValueError, "Poisson m must be >= 0."
return igamc(k+1, m)

def pdtrc(k, m):
```
```    if x < 0.0:
raise ZeroDivisionError, "x must be at least 0."
return igamc(b, a * x)

#note: ndtri for the normal distribution is already imported
```