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rebmix (version 2.16.0)

Finite Mixture Modeling, Clustering & Classification

Description

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.

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Version

Install

install.packages('rebmix')

Monthly Downloads

641

Version

2.16.0

License

GPL (>= 2)

Maintainer

Marko Nagode

Last Published

July 10th, 2024

Functions in rebmix (2.16.0)

EM.Control-class

Class "EM.Control"

Partition Coefficient

Total of Positive Relative Deviations

Extracts Chunk from Train and Test Datasets

Class "RCLRMIX"

Integrated Classification Likelihood Criterion

RCLRMIX-methods

Predicts Cluster Membership Based Upon a Model Trained by REBMIX

RCLS.chunk-class

Class "RCLS.chunk"

Minimum Description Length

Approximate Integrated Classification Likelihood Criterion

Class "RCLSMIX"

Parametric or Nonparametric Bootstrap for Standard Error and Coefficient of Variation Estimation

RCLSMIX-methods

Predicts Class Membership Based Upon a Model Trained by REBMIX

RNGMIX.Theta-class

Class "RNGMIX.Theta"

Random Univariate or Multivariate Finite Mixture Generation

Plots RNGMIX, REBMIX, RCLRMIX and RCLSMIX Output

REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation

REBMIX.boot-class

Class "REBMIX.boot"

Sum of Squares Error

Class "RNGMIX"

Class "REBMIX"

Empirical Density Calculation

chistogram-methods

Compact Histogram Calculation

Binning of Data

Bearings Faults Detection Data

fhistogram-methods

Fast Histogram Calculation

Sequence of Bins or Nearest Neighbours Generation

Empirical Distribution Function Calculation

Predictive Marginal Density Calculation

labelmoments-methods

Label Image Moments

optbins-methods

Optimal Numbers of Bins Calculation

Steel Plates Faults Recognition Data

Splits Dataset into Train and Test Datasets

sensorlessdrive

Sensorless Drive Faults Detection Data

mergelabels-methods

Merge Labels Based on Probability Adjacency Matrix

Weibull Dataset 8.1

mapclusters-methods

Wine Recognition Data

rebmix-internal

Internal rebmix Functions, Methods and Classes

Predictive Marginal Distribution Function Calculation

Weibull-normal Simulated Dataset

Histogram-class

Class "Histogram"

Akaike Information Criterion

Predicts Class Membership Based Upon the Best First Search Algorithm

EM Algorithm for Univariate or Multivariate Finite Mixture Estimation

Hannan-Quinn Information Criterion

Bayesian Information Criterion

Classification Likelihood Criterion

Approximate Weight of Evidence Criterion

EMMIX.Theta-class

Class "EMMIX.Theta"