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RMBC  

Robust Model Based Clustering
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("RMBC", "0.1.0")



Attach the package and use:
library("RMBC")
Maintained by
Juan Domingo Gonzalez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-22
Latest Update:
Description:
A robust clustering algorithm (Model-Based) similar to Expectation Maximization for finite mixture normal distributions is implemented, its main advantage is that the estimator is resistant to outliers, that means that results of parameter estimation are still correct when there are atypical values in the sample (see Gonzalez, Maronna, Yohai and Zamar (2021) ).
How to cite:
Juan Domingo Gonzalez (2021). RMBC: Robust Model Based Clustering. R package version 0.1.0, https://cran.r-project.org/web/packages/RMBC. Accessed 05 Mar. 2026.
Previous versions and publish date:
0.1.0 (2021-07-22 08:40)
Other packages that cited RMBC R package
View RMBC citation profile
Other R packages that RMBC depends, imports, suggests or enhances
Complete documentation for RMBC
Functions, R codes and Examples using the RMBC R package
Some associated functions: RMBC . RMBCaux . is_in_gr . klfor2normals . phytoplankton_acoustic_data . quad_disc . robustINIT . sumkl . weightW . weightedMscale . weightedSestimator . 
Some associated R codes: RMBC.R . RMBCaux.R . is_in_gr.R . phytoplankton_acoustic_data.R . quad_disc.R . robustINIT.R . utils.R . weightedMscale.R . weightedSestimator.R .  Full RMBC package functions and examples
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