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rebmix (version 2.14.2)

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

386

Version

2.14.2

License

GPL (>= 2)

Maintainer

Marko Nagode

Last Published

August 17th, 2022

Functions in rebmix (2.14.2)

Classification Likelihood Criterion

Hannan-Quinn Information Criterion

Akaike Information Criterion

Approximate Weight of Evidence Criterion

EM.Control-class

Class "EM.Control"

Total of Positive Relative Deviations

Extracts Chunk from Train and Test Datasets

Predicts Class Membership Based Upon the Best First Search Algorithm

Bayesian Information Criterion

Class "RCLSMIX"

Class "RCLRMIX"

Histogram-class

Class "Histogram"

RCLRMIX-methods

Predicts Cluster Membership Based Upon a Model Trained by REBMIX

EM Algorithm for Univariate or Multivariate Finite Mixture Estimation

RCLSMIX-methods

Predicts Class Membership Based Upon a Model Trained by REBMIX

REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation

RCLS.chunk-class

Class "RCLS.chunk"

Empirical Density Calculation

REBMIX.boot-class

Class "REBMIX.boot"

Predictive Marginal Density Calculation

Class "REBMIX"

Plots RNGMIX, REBMIX, RCLRMIX and RCLSMIX Output

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

fhistogram-methods

Fast Histogram Calculation

Integrated Classification Likelihood Criterion

EMMIX.Theta-class

Class "EMMIX.Theta"

Approximate Integrated Classification Likelihood Criterion

Minimum Description Length

Binning of Data

Partition Coefficient

Class "RNGMIX"

chistogram-methods

Compact Histogram Calculation

RNGMIX.Theta-class

Class "RNGMIX.Theta"

Sum of Squares Error

Random Univariate or Multivariate Finite Mixture Generation

Bearings Faults Detection Data

Sequence of Bins or Nearest Neighbours Generation

Predictive Marginal Distribution Function Calculation

Steel Plates Faults Recognition Data

Wine Recognition Data

rebmix-internal

Internal rebmix Functions

sensorlessdrive

Sensorless Drive Faults Detection Data

mapclusters-methods

Splits Dataset into Train and Test Datasets

optbins-methods

Optimal Numbers of Bins Calculation

Empirical Distribution Function Calculation

Weibull Dataset 8.1

Weibull-normal Simulated Dataset