| 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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