Model Based Clustering for Mixed Data

Byar | Byar prostate cancer data set. |

clustMD | Model Based Clustering for Mixed Data |

clustMDlist | Model Based Clustering for Mixed Data |

clustMD-package | Model based clustering for mixed data: clustMD |

clustMDparallel | Run multiple clustMD models in parallel |

clustMDparcoord | Parallel coordinates plot adapted for 'clustMD' output |

dtmvnom | Return the mean and covariance matrix of a truncated... |

E.step | E-step of the (MC)EM algorithm |

getOutput_clustMDparallel | Extracts relevant output from 'clustMDparallel' object |

modal.value | Calculate the mode of a sample |

M.step | M-step of the (MC)EM algorithm |

npars_clustMD | Calculates the number of free parameters for the 'clustMD'... |

ObsLogLikelihood | Approximates the observed log likelihood. |

patt.equal | Check if response patterns are equal |

perc.cutoffs | Calculates the threshold parameters for ordinal variables. |

plot.clustMD | Plotting method for objects of class 'clustMD' |

plot.clustMDparallel | Summary plots for a clustMDparallel object |

print.clustMD | Print basic details of 'clustMD' object. |

print.clustMDparallel | Print basic details of 'clustMDparallel' object |

qfun | Helper internal function for 'dtmvnom()' |

stable.probs | Stable computation of the log of a sum |

summary.clustMD | Summarise 'clustMD' object |

summary.clustMDparallel | Prints a summary of a clustMDparallel object to screen. |

vec.outer | Calculate the outer product of a vector with itself |

z.moments | Calculates the first and second moments of the latent data |

z.moments_diag | Calculates the first and second moments of the latent data... |

z.nom.diag | Transforms Monte Carlo simulated data into categorical data.... |

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