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An R Code for Implementing Non-hierarchical Algorithm for Clustering of Probability Density Functions

Authors: 

Ngoc Diem TRAN, Tom VINANT, Théo Marc COLOMBANI, Kieu Diem HO*

Source title: 
Journal of Advanced Engineering and Computation, 2(3): 174-187, 2018 (Scopus)
Academic year of acceptance: 
2018-2019
Abstract: 

This paper aims to present a code for implementation of non-hierarchical algorithm to cluster probability density functions in one dimension for the first time in R environment. The structure of code consists of 2 primary steps: executing the main clustering algorithm and evaluating the clustering quality. The code is validated on one simulated data set and two applications. The numerical results obtained are highly compatible with that on MATLAB software regarding computational time. Notably, the code mainly serves for educational purpose and desires to extend the availability of algorithm in several environments so as having multiple choices for whom interested in clustering.