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>.

Goodness-of-Fit Tests using Kernelized Stein Discrepancy

package-ubuntu-20.04-r-4.0.5#cran#KSD-1.0.1

<p>We generate a standard normal distribution,
and add varying gaussian noise to this dataset and see the change in pvalues.
</p>

package-ubuntu-20.04-r-4.0.5#cran#KSD-1.0.1#docs#demo_normal_performance

demo_normal_performance

Description

Usage

KSD

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