Some Basic Functions for Tree Representations of Bayesian Markov Chain Monte Carlo Clustering

The paper contains description of the implementation of C code for tree representation of Markov Chain Monte Carlo(MCMC) clustering. The aim of the code is to produce results which helps in visual representation of the most frequent pattern, its agglomerations and divisions and thus helps in constructing a tree also called as dendrogram. It illustrates the mergers or divisions which have been made at successive levels. The paper explains codes for various code functions used for finding the most frequent patterns, its agglomerations and divisions from the labels generated by Markov Chain Monte Carlo Simulations. They have been implemented in C and attached to R statistical software. The algorithmic analysis of code and running time analysis has been done with the help of certain test datasets in later section of the report. The following section of the paper contains description of the C files, the explanation of the function implemented in them and its linkage to R so that C function can be called from R for speeding up the execution of the code.