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salso  

Search Algorithms and Loss Functions for Bayesian Clustering
View on CRAN: Click here


Download and install salso package within the R console
Install from CRAN:
install.packages("salso")

Install from Github:
library("remotes")
install_github("cran/salso")

Install by package version:
library("remotes")
install_version("salso", "0.3.42")



Attach the package and use:
library("salso")
Maintained by
David B. Dahl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-09-21
Latest Update: 2023-07-17
Description:
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, M
How to cite:
David B. Dahl (2019). salso: Search Algorithms and Loss Functions for Bayesian Clustering. R package version 0.3.42, https://cran.r-project.org/web/packages/salso. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.2 (2019-09-21 13:40), 0.1.3 (2019-09-27 18:30), 0.1.9 (2019-11-29 20:50), 0.1.11 (2020-01-07 21:20), 0.1.16 (2020-02-07 20:00), 0.2.3 (2020-11-09 20:00), 0.2.5 (2020-11-19 14:10), 0.2.15 (2021-03-10 16:40), 0.2.20 (2021-03-28 00:20), 0.2.22 (2021-05-13 09:40), 0.2.23 (2021-08-13 06:40), 0.3.0 (2021-12-06 19:20), 0.3.27 (2022-12-03 01:40), 0.3.29 (2022-12-20 07:30), 0.3.35 (2023-07-17 22:20), 0.3.41 (2024-09-07 02:10)
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