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 |
| 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 |
| 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 |