R package chgdetn: Sequential Change-Point Detection, Analysis, Simulation
Provides tools for change-point detection in the sequential setting and simulation experiments.
We assume that the observations are independent and such that each follows a known common distribution before the change, and a different common distribution after the change. We have proposed a statistic-based stopping rule for continuous and binary data with known post-changed distributions. For continuous data with unknown post-changed distributions, we have developed a generalized Bayesian stopping rule implemented via the Sequential Monte Carlo algorithm. The proposed methods utilize the Hyvärinen score to improve computation efficiency when the model is known up to a factor of normalizing constant.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.