scipy.special.nrdtrimn#

scipy.special.nrdtrimn(p, std, x, out=None) = <ufunc 'nrdtrimn'>#

Calculate mean of normal distribution given other params.

Parameters:

parray_like: CDF values, in range (0, 1].
stdarray_like: Standard deviation.
xarray_like: Quantiles, i.e. the upper limit of integration.
outndarray, optional: Optional output array for the function results

Returns:

mnscalar or ndarray: The mean of the normal distribution.

See also

scipy.stats.norm: Normal distribution
ndtr: Standard normal cumulative probability distribution
ndtri: Inverse of standard normal CDF with respect to quantile
nrdtrisd: Inverse of normal distribution CDF with respect to standard deviation

Examples

nrdtrimn can be used to recover the mean of a normal distribution if we know the CDF value p for a given quantile x and the standard deviation std. First, we calculate the normal distribution CDF for an exemplary parameter set.

>>> from scipy.stats import norm
>>> mean = 3.
>>> std = 2.
>>> x = 6.
>>> p = norm.cdf(x, loc=mean, scale=std)
>>> p
0.9331927987311419

Verify that nrdtrimn returns the original value for mean.

>>> from scipy.special import nrdtrimn
>>> nrdtrimn(p, std, x)
3.0000000000000004