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... |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.