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mmb  

Arbitrary Dependency Mixed Multivariate Bayesian Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mmb", "0.13.3")



Attach the package and use:
library("mmb")
Maintained by
Sebastian Hönel
[Scholar Profile | Author Map]
First Published: 2020-09-23
Latest Update: 2020-09-23
Description:
Supports Bayesian models with full and partial (hence arbitrary) dependencies between random variables. Discrete and continuous variables are supported, and conditional joint probabilities and probability densities are estimated using Kernel Density Estimation (KDE). The full general form, which implements an extension to Bayes' theorem, as well as the simple form, which is just a Bayesian network, both support regression through segmentation and KDE and estimation of probability or relative likelihood of discrete or continuous target random variables. This package also provides true statistical distance measures based on Bayesian models. Furthermore, these measures can be facilitated on neighborhood searches, and to estimate the similarity and distance between data points. Related work is by Bayes (1763) and by Scutari (2010) .
How to cite:
Sebastian Hönel (2020). mmb: Arbitrary Dependency Mixed Multivariate Bayesian Models. R package version 0.13.3, https://cran.r-project.org/web/packages/mmb. Accessed 04 Apr. 2025.
Previous versions and publish date:
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Complete documentation for mmb
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