demo_simple_gaussian

truemu

standard deviation of true distribution

truesd

noisemu

standard deviation of gaussian noise to add

noisesd

We generate a gaussian distribution with given parameters,
and add noise to this dataset. We then compute the score
of each dataset for the original true distribution.

An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <arXiv:1602.03253>.

demo_simple_gaussian: Tests 1-dimensional Gaussian Distribution with customized parameters

Description

Usage

Arguments