Normal distribution

Normal and truncated normal distributions.

Notes

The probability density function for standard normal distribution is:

.. math::

f(x) = \frac{\exp(-x^2/2)}{\sqrt{2\pi}}

for a real number :math:x.

The probability density function for normal distribution with arbitrary mean and standard deviation is:

.. math::

f(x)=\frac{1}{\sqrt{2\pi}\sigma}e^{-(x-\mu)^{2}/2\sigma^{2}}

for :math:-\infty < \mu < \infty and :math:\sigma > 0.

Examples

Methods

=================================================== ================================= Method Description =================================================== ================================= normalPDF(x[, mean, std]) Probability density function of the standard normal distribution. normalCDF(x[, mean, std]) Cumulative distribution function of the standard normal distribution. normalPPF(x[, mean, std]) Percent point function of the standard normal distribution. normalSampleFloat64(m[, mean, std]) Sampling from the standard normal distribution. truncNormalPDF(x, mean, std, start, end) Probability density function for truncated normal distribution truncNormalCDF(x, mean, std, start, end) Cumulative density function for truncated normal distribution truncNormalPPF(x, mean, std, start, end) Percentage point function (inverse of cdf) for truncated normal distribution truncNormalSampleFloat64(m, mean, std, start, end) Sampling from the truncated normal distribution =================================================== =================================