salso

The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) doi:10.1080/10618600.2022.2069779.

Last 30 days

This package has been downloaded 913 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 22 times.

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Last 365 days

This package has been downloaded 96,055 times in the last 365 days. This work is reaching a lot of screens. A significant achievement indeed! The day with the most downloads was Nov 01, 2024 with 12,363 downloads.

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