Finite Mixture Modeling, Clustering & Classification
Akaike Information Criterion
Approximate Weight of Evidence Criterion
Predicts Class Membership Based Upon the Best First Search Algorithm
Bayesian Information Criterion
Binning of Data
Class "Histogram"
Hannan-Quinn Information Criterion
Integrated Classification Likelihood Criterion
Approximate Integrated Classification Likelihood Criterion
Sequence of Bins or Nearest Neighbours Generation
Partition Coefficient
Empirical Distribution Function Calculation
Predictive Marginal Distribution Function Calculation
Total of Positive Relative Deviations
Class "RCLRMIX"
Predicts Cluster Membership Based Upon a Model Trained by REBMIX
Class "RCLS.chunk"
Extracts Chunk from Train and Test Datasets
Class "RNGMIX.Theta"
Splits Dataset into Train and Test Datasets
Sum of Squares Error
Compact Histogram Calculation
Classification Likelihood Criterion
Empirical Density Calculation
Predictive Marginal Density Calculation
Class "EM.Control"
EM Algorithm for Univariate or Multivariate Finite Mixture Estimation
Class "EMMIX.Theta"
Fast Histogram Calculation
Label Image Moments
Log Likelihood
Map Clusters
Minimum Description Length
Merge Labels Based on Probability Adjacency Matrix
Optimal Numbers of Bins Calculation
Class "RCLSMIX"
Predicts Class Membership Based Upon a Model Trained by REBMIX
Class "REBMIX"
Internal rebmix Functions, Methods and Classes
Class "REBMIX.boot"
Parametric or Nonparametric Bootstrap for Standard Error and Coefficie...
Plots RNGMIX, REBMIX, RCLRMIX and RCLSMIX Output
REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimat...
Class "RNGMIX"
Random Univariate or Multivariate Finite Mixture Generation
Random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, Gumbel, binomial, Poisson, Dirac, uniform or circular von Mises parametric families.