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PEkit  

Partition Exchangeability Toolkit
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PEkit", "1.0.0.1000")



Attach the package and use:
library("PEkit")
Maintained by
Ali Amiryousefi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-22
Latest Update: 2021-11-22
Description:
Bayesian supervised predictive classifiers, hypothesis testing, and parametric estimation under Partition Exchangeability are implemented. The two classifiers presented are the marginal classifier (that assumes test data is i.i.d.) next to a more computationally costly but accurate simultaneous classifier (that finds a labelling for the entire test dataset at once based on simultanous use of all the test data to predict each label). We also provide the Maximum Likelihood Estimation (MLE) of the only underlying parameter of the partition exchangeability generative model as well as hypothesis testing statistics for equality of this parameter with a single value, alternative, or multiple samples. We present functions to simulate the sequences from Ewens Sampling Formula as the realisation of the Poisson-Dirichlet distribution and their respective probabilities.
How to cite:
Ali Amiryousefi (2021). PEkit: Partition Exchangeability Toolkit. R package version 1.0.0.1000, https://cran.r-project.org/web/packages/PEkit. Accessed 15 Jul. 2026.
Previous versions and publish date:
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Other packages that cited PEkit R package
View PEkit citation profile
Other R packages that PEkit depends, imports, suggests or enhances
Complete documentation for PEkit
Functions, R codes and Examples using the PEkit R package
Some associated functions: MLEp.bsci . MLEp . abundance . classifier.fit . dPD . is.PD . mult.sample.test . rPD . sample.test . tMarLab . tSimLab . two.sample.test . 
Some associated R codes: Classifier.R . Neutrality_tests.R . PD_distribution.R . Parameter_estimation_and_hypothesis_testing.R . utils.R .  Full PEkit package functions and examples
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