Simulating Data to Study Performance of Clustering Algorithms
Simulation of Gaussian Finite Mixture Models
Classification Proportion
Mixture Simulation based on generalized overlap of Maitra
Mixture Simulation
Overlap
Generalized overlap of Maitra
Parallel Distribution Plot
Permutations
Functions for Printing or Summarizing Objects
Rand's Index
Dataset Simulation
Variation of Information
The utility of this package is in simulating mixtures of Gaussian distributions with different levels of overlap between mixture components. Pairwise overlap, defined as a sum of two misclassification probabilities, measures the degree of interaction between components and can be readily employed to control the clustering complexity of datasets simulated from mixtures. These datasets can then be used for systematic performance investigation of clustering and finite mixture modeling algorithms. Among other capabilities of 'MixSim', there are computing the exact overlap for Gaussian mixtures, simulating Gaussian and non-Gaussian data, simulating outliers and noise variables, calculating various measures of agreement between two partitionings, and constructing parallel distribution plots for the graphical display of finite mixture models.