A B C D E F G H I K L M O P R S T W
| adult | Adult Dataset | 
| AIC | Akaike Information Criterion | 
| AIC-method | Akaike Information Criterion | 
| AIC-methods | Akaike Information Criterion | 
| AIC3 | Akaike Information Criterion | 
| AIC3-method | Akaike Information Criterion | 
| AIC3-methods | Akaike Information Criterion | 
| AIC4 | Akaike Information Criterion | 
| AIC4-method | Akaike Information Criterion | 
| AIC4-methods | Akaike Information Criterion | 
| AICc | Akaike Information Criterion | 
| AICc-method | Akaike Information Criterion | 
| AICc-methods | Akaike Information Criterion | 
| AWE | Approximate Weight of Evidence Criterion | 
| AWE-method | Approximate Weight of Evidence Criterion | 
| AWE-methods | Approximate Weight of Evidence Criterion | 
| bearings | Bearings Faults Detection Data | 
| BFSMIX | Predicts Class Membership Based Upon the Best First Search Algorithm | 
| BFSMIX-method | Predicts Class Membership Based Upon the Best First Search Algorithm | 
| BFSMIX-methods | Predicts Class Membership Based Upon the Best First Search Algorithm | 
| BIC | Bayesian Information Criterion | 
| BIC-method | Bayesian Information Criterion | 
| BIC-methods | Bayesian Information Criterion | 
| bins | Binning of Data | 
| bins-method | Binning of Data | 
| bins-methods | Binning of Data | 
| boot | Parametric or Nonparametric Bootstrap for Standard Error and Coefficient of Variation Estimation | 
| boot-method | Parametric or Nonparametric Bootstrap for Standard Error and Coefficient of Variation Estimation | 
| boot-methods | Parametric or Nonparametric Bootstrap for Standard Error and Coefficient of Variation Estimation | 
| CAIC | Akaike Information Criterion | 
| CAIC-method | Akaike Information Criterion | 
| CAIC-methods | Akaike Information Criterion | 
| chistogram | Compact Histogram Calculation | 
| chistogram-method | Compact Histogram Calculation | 
| chistogram-methods | Compact Histogram Calculation | 
| chunk | Extracts Chunk from Train and Test Datasets | 
| chunk-method | Extracts Chunk from Train and Test Datasets | 
| chunk-methods | Extracts Chunk from Train and Test Datasets | 
| CLC | Classification Likelihood Criterion | 
| CLC-method | Classification Likelihood Criterion | 
| CLC-methods | Classification Likelihood Criterion | 
| demix | Empirical Density Calculation | 
| demix-method | Empirical Density Calculation | 
| demix-methods | Empirical Density Calculation | 
| dfmix | Predictive Marginal Density Calculation | 
| dfmix-method | Predictive Marginal Density Calculation | 
| dfmix-methods | Predictive Marginal Density Calculation | 
| EM.Control-class | Class '"EM.Control"' | 
| EMMIX | EM Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| EMMIX-method | EM Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| EMMIX-methods | EM Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| EMMIX.Theta-class | Class '"EMMIX.Theta"' | 
| EMMVNORM.Theta-class | Class '"EMMIX.Theta"' | 
| fhistogram | Fast Histogram Calculation | 
| fhistogram-method | Fast Histogram Calculation | 
| fhistogram-methods | Fast Histogram Calculation | 
| galaxy | Galaxy Dataset | 
| Histogram-class | Class '"Histogram"' | 
| HQC | Hannan-Quinn Information Criterion | 
| HQC-method | Hannan-Quinn Information Criterion | 
| HQC-methods | Hannan-Quinn Information Criterion | 
| ICL | Integrated Classification Likelihood Criterion | 
| ICL-method | Integrated Classification Likelihood Criterion | 
| ICL-methods | Integrated Classification Likelihood Criterion | 
| ICLBIC | Approximate Integrated Classification Likelihood Criterion | 
| ICLBIC-method | Approximate Integrated Classification Likelihood Criterion | 
| ICLBIC-methods | Approximate Integrated Classification Likelihood Criterion | 
| iris | Iris Data Set | 
| kseq | Sequence of Bins or Nearest Neighbours Generation | 
| labelmoments | Label Image Moments | 
| labelmoments-method | Label Image Moments | 
| labelmoments-methods | Label Image Moments | 
| logL | Log Likelihood | 
| logL-method | Log Likelihood | 
| logL-methods | Log Likelihood | 
| mapclusters | Map Clusters | 
| mapclusters-method | Map Clusters | 
| mapclusters-methods | Map Clusters | 
| MDL2 | Minimum Description Length | 
| MDL2-method | Minimum Description Length | 
| MDL2-methods | Minimum Description Length | 
| MDL5 | Minimum Description Length | 
| MDL5-method | Minimum Description Length | 
| MDL5-methods | Minimum Description Length | 
| mergelabels | Merge Labels Based on Probability Adjacency Matrix | 
| mergelabels-method | Merge Labels Based on Probability Adjacency Matrix | 
| mergelabels-methods | Merge Labels Based on Probability Adjacency Matrix | 
| optbins | Optimal Numbers of Bins Calculation | 
| optbins-method | Optimal Numbers of Bins Calculation | 
| optbins-methods | Optimal Numbers of Bins Calculation | 
| PC | Partition Coefficient | 
| PC-method | Partition Coefficient | 
| PC-methods | Partition Coefficient | 
| pemix | Empirical Distribution Function Calculation | 
| pemix-method | Empirical Distribution Function Calculation | 
| pemix-methods | Empirical Distribution Function Calculation | 
| pfmix | Predictive Marginal Distribution Function Calculation | 
| pfmix-method | Predictive Marginal Distribution Function Calculation | 
| pfmix-methods | Predictive Marginal Distribution Function Calculation | 
| plot-method | Plots RNGMIX, REBMIX, RCLRMIX and RCLSMIX Output | 
| plot-methods | Plots RNGMIX, REBMIX, RCLRMIX and RCLSMIX Output | 
| PRD | Total of Positive Relative Deviations | 
| PRD-method | Total of Positive Relative Deviations | 
| PRD-methods | Total of Positive Relative Deviations | 
| RCLRMIX | Predicts Cluster Membership Based Upon a Model Trained by REBMIX | 
| RCLRMIX-class | Class '"RCLRMIX"' | 
| RCLRMIX-method | Predicts Cluster Membership Based Upon a Model Trained by REBMIX | 
| RCLRMIX-methods | Predicts Cluster Membership Based Upon a Model Trained by REBMIX | 
| RCLRMVNORM-class | Class '"RCLRMIX"' | 
| RCLS.chunk-class | Class '"RCLS.chunk"' | 
| RCLSMIX | Predicts Class Membership Based Upon a Model Trained by REBMIX | 
| RCLSMIX-class | Class '"RCLSMIX"' | 
| RCLSMIX-method | Predicts Class Membership Based Upon a Model Trained by REBMIX | 
| RCLSMIX-methods | Predicts Class Membership Based Upon a Model Trained by REBMIX | 
| RCLSMVNORM-class | Class '"RCLSMIX"' | 
| REBMIX | REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| REBMIX-class | Class '"REBMIX"' | 
| REBMIX-method | REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| REBMIX-methods | REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| REBMIX.boot-class | Class '"REBMIX.boot"' | 
| REBMVNORM-class | Class '"REBMIX"' | 
| REBMVNORM.boot-class | Class '"REBMIX.boot"' | 
| RNGMIX | Random Univariate or Multivariate Finite Mixture Generation | 
| RNGMIX-class | Class '"RNGMIX"' | 
| RNGMIX-method | Random Univariate or Multivariate Finite Mixture Generation | 
| RNGMIX-methods | Random Univariate or Multivariate Finite Mixture Generation | 
| RNGMIX.Theta-class | Class '"RNGMIX.Theta"' | 
| RNGMVNORM-class | Class '"RNGMIX"' | 
| RNGMVNORM.Theta-class | Class '"RNGMIX.Theta"' | 
| sensorlessdrive | Sensorless Drive Faults Detection Data | 
| show-method | Class '"EM.Control"' | 
| show-method | Class '"EMMIX.Theta"' | 
| show-method | Predicts Cluster Membership Based Upon a Model Trained by REBMIX | 
| show-method | Extracts Chunk from Train and Test Datasets | 
| show-method | Predicts Class Membership Based Upon a Model Trained by REBMIX | 
| show-method | REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| show-method | Parametric or Nonparametric Bootstrap for Standard Error and Coefficient of Variation Estimation | 
| show-method | Random Univariate or Multivariate Finite Mixture Generation | 
| show-method | Class '"RNGMIX.Theta"' | 
| split | Splits Dataset into Train and Test Datasets | 
| split-method | Splits Dataset into Train and Test Datasets | 
| split-methods | Splits Dataset into Train and Test Datasets | 
| SSE | Sum of Squares Error | 
| SSE-method | Sum of Squares Error | 
| SSE-methods | Sum of Squares Error | 
| steelplates | Steel Plates Faults Recognition Data | 
| summary-method | Predicts Cluster Membership Based Upon a Model Trained by REBMIX | 
| summary-method | Predicts Class Membership Based Upon a Model Trained by REBMIX | 
| summary-method | REBMIX Algorithm for Univariate or Multivariate Finite Mixture Estimation | 
| summary-method | Parametric or Nonparametric Bootstrap for Standard Error and Coefficient of Variation Estimation | 
| truck | Truck Dataset | 
| weibull | Weibull Dataset 8.1 | 
| weibullnormal | Weibull-normal Simulated Dataset | 
| wine | Wine Recognition Data |