Sequential Method for Classification and Generalized Estimating Equations Problem

A_optimal_cat | Get the most informative subjects from unlabeled dataset for... |

A_optimal_ord | Get the most informative subjects from unlabeled dataset for... |

ase_seq_logit | variable selection and stopping criterion |

D_optimal | Get the most informative subjects for the clustered data |

evaluateGEEModel | The adaptive shrinkage estimate for generalized estimating... |

genBin | Generate the correlated binary response data for discrete... |

gen_bin_data | generate the data used for the model experiment |

genCorMat | Generate the correlation matrix for the clusteded data |

gen_GEE_data | Generate the datasets with clusters |

gen_multi_data | Generate the training data and testing data for the... |

getMH | Get the matrices M and H for the clustered data for the GEE... |

getWH | Get the matrices W and H for the categorical case |

getWH_ord | Get the matrices W and H for the ordinal case |

init_multi_data | Generate the labeled and unlabeled datasets |

is_stop_ASE | Determining whether to stop choosing sample |

logit_model | the individualized binary logistic regression for categorical... |

logit_model_ord | the individualized binary logistic regression for ordinal... |

print.seqbin | Print the results by the binary logistic regression model |

print.seqGEE | Print the results by the generalized estimating equations. |

print.seqmulti | Print the results by the multi-logistic regression model |

QIC | Calculate quasi-likelihood under the independence model... |

seq_bin_model | The sequential logistic regression model for binary... |

seq_cat_model | The sequential logistic regression model for... |

seq_GEE_model | The The sequential method for generalized estimating... |

seq_ord_model | The sequential logistic regression model for... |

update_data_cat | Add the new sample into labeled dataset from unlabeled... |

update_data_ord | Add the new sample into labeled dataset from unlabeled... |

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