Did I find the right examples for you? yes no      Crawl my project      Python Jobs

# cogent.maths.stats.special.ndtri

All Samples(11)  |  Call(5)  |  Derive(0)  |  Import(6)

```"""
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
```

```"""
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
```

```from numpy.random import normal
from cogent.maths.stats.distribution import z_high
from cogent.maths.stats.special import ndtri
from warnings import warn
```
```    #Start by calculating Z-scores using the inverse normal distribution,
#starting with the given confidence value
z = ndtri(confidence)
#print "Z:",z
#Now we need to fit a normal distribution given the confidence
```

```#!/usr/bin/env python
"""Unit tests for special functions used in statistics.
"""
from cogent.util.unit_test import TestCase, main
from cogent.maths.stats.special import permutations, permutations_exact, \
```
```2.32634787404,
]
obs = [ndtri(i/100.0) for i in range(100)]
self.assertFloatEqual(obs, exp)

```

```#!/usr/bin/env python
"""Unit tests for special functions used in statistics.
"""
from cogent.util.unit_test import TestCase, main
from cogent.maths.stats.special import permutations, permutations_exact, \
```
```2.32634787404,
]
obs = [ndtri(i/100.0) for i in range(100)]
self.assertFloatEqual(obs, exp)

```

```from cogent.app.util import get_tmp_filename
from cogent.util.misc import remove_files
from cogent.maths.stats.special import ndtri
from warnings import catch_warnings
from picrust.predict_traits  import assign_traits_to_tree,\
```
```    def test_fit_normal_to_confidence_interval(self):
"""fit_normal_to_confidence_interval should return a mean and variance given CI"""

#Lets use a normal distribution to generate test values
normal_95 = ndtri(0.95)
```
```
#An alternative normal:
normal_99 = ndtri(0.99)
mean = 5.0
upper = mean + normal_99
```