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rebmix (version 2.10.2)

Finite Mixture Modeling, Clustering & Classification

Description

R functions for random univariate and multivariate finite mixture model generation, estimation, clustering and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, binomial, Poisson, Dirac or circular von Mises parametric families.

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Version

Install

install.packages('rebmix')

Monthly Downloads

413

Version

2.10.2

License

GPL (>= 2)

Maintainer

Marko Nagode

Last Published

May 22nd, 2018

Functions in rebmix (2.10.2)

Predicts Class Membership Based Upon the Best First Search Algorithm

Akaike Information Criterion

Predictive Marginal Density Calculation

REBMIX.boot-class

Class "REBMIX.boot"

Empirical Distribution Function Calculation

Sum of Squares Error

rebmix-internal

Internal rebmix Functions

Class "RNGMIX"

Random Univariate or Multivariate Finite Mixture Generation

Weibull-normal Simulated Dataset

Wine Recognition Data

Splits Dataset into Train and Test Datasets

Classification Likelihood Criterion

Minimum Description Length

Hannan-Quinn Information Criterion

RCLS.chunk-class

Class "RCLS.chunk"

RCLRMIX-methods

Predicts Cluster Membership Based Upon a Model Trained by REBMIX

Predictive Cluster Membership

Integrated Classification Likelihood Criterion

Total of Positive Relative Deviations

Class "RCLRMIX"

Approximate Integrated Classification Likelihood Criterion

Extracts Chunk from Train and Test Datasets

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

Predictive Marginal Distribution Function Calculation

Plots RNGMIX, REBMIX, RCLRMIX and RCLSMIX Output

REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation

Class "REBMIX"

Empirical Density Calculation

Prints Univariate or Multivariate REBMIX Coefficients

Partition Coefficient

Sequence of Bins or Nearest Neighbours Generation

Weibull Dataset 8.1

Approximate Weight of Evidence Criterion

Class "RCLSMIX"

RCLSMIX-methods

Predicts Class Membership Based Upon a Model Trained by REBMIX

Bayesian Information Criterion