scipy.special.nrdtrisd#

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

Calculate standard deviation of normal distribution given other params.

Parameters:

mnscalar or ndarray: The mean of the normal distribution.
parray_like: CDF values, in range (0, 1].
xarray_like: Quantiles, i.e. the upper limit of integration.
outndarray, optional: Optional output array for the function results

Returns:

stdscalar or ndarray: Standard deviation.

See also

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

Examples

nrdtrisd can be used to recover the standard deviation of a normal distribution if we know the CDF value p for a given quantile x and the mean mn. 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 nrdtrisd returns the original value for std.

>>> from scipy.special import nrdtrisd
>>> nrdtrisd(mean, p, x)
2.0000000000000004