changepoints

Performs a series of offline and/or online change-point detection algorithms for 1) univariate mean: doi:10.1214/20-EJS1710, doi:10.48550/arXiv.2006.03283; 2) univariate polynomials: doi:10.1214/21-EJS1963; 3) univariate and multivariate nonparametric settings: doi:10.1214/21-EJS1809, doi:10.1109/TIT.2021.3130330; 4) high-dimensional covariances: doi:10.3150/20-BEJ1249; 5) high-dimensional networks with and without missing values: doi:10.1214/20-AOS1953, doi:10.48550/arXiv.2101.05477, doi:10.48550/arXiv.2110.06450; 6) high-dimensional linear regression models: doi:10.48550/arXiv.2010.10410, doi:10.48550/arXiv.2207.12453; 7) high-dimensional vector autoregressive models: doi:10.48550/arXiv.1909.06359; 8) high-dimensional self exciting point processes: doi:10.48550/arXiv.2006.03572; 9) dependent dynamic nonparametric random dot product graphs: doi:10.48550/arXiv.1911.07494; 10) univariate mean against adversarial attacks: doi:10.48550/arXiv.2105.10417.

Last 30 days

This package has been downloaded 346 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,376 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Aug 22, 2024 with 29 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.