pymc_icdf.md

References

• Issue #6612: pymc-devs/pymc#6612
• def check_icdf_value is in this file: dist_math
  • from pymc.distributions.dist_math import (check_icdf_parameters, check_icdf_value,

Workflow

1. Determine if the distribution is Continous or Discrete
2. The files that have the code are here:
   • Continous distributions: https://github.com/pymc-devs/pymc/blob/main/pymc/distributions/continuous.py
   • Discrete distributions: https://github.com/pymc-devs/pymc/blob/main/pymc/distributions/discrete.py

Continuous: Example

There is a class for each distribution:

class Normal(Continuous):
    r"""
    Univariate normal log-likelihood.
    The pdf of this distribution is
    .. math::
       f(x \mid \mu, \tau) =
           \sqrt{\frac{\tau}{2\pi}}
           \exp\left\{ -\frac{\tau}{2} (x-\mu)^2 \right\}

Within this class there is :

    def icdf(value, mu, sigma):
        res = mu + sigma * -np.sqrt(2.0) * pt.erfcinv(2 * value)
        res = check_icdf_value(res, value)
        return check_icdf_parameters(
            res,
            sigma > 0,
            msg="sigma > 0",
        )