Sequential Method for Classification and Generalized Estimating Equations Problem
Get the most informative subjects from unlabeled dataset for the categ...
Get the most informative subjects from unlabeled dataset for the ordin...
variable selection and stopping criterion
Get the most informative subjects for the clustered data
The adaptive shrinkage estimate for generalized estimating equations
generate the data used for the model experiment
Generate the datasets with clusters
Generate the training data and testing data for the categorical and or...
Generate the correlated binary response data for discrete case
Generate the correlation matrix for the clusteded data
Get the matrices M and H for the clustered data for the GEE case
Get the matrices W and H for the categorical case
Get the matrices W and H for the ordinal case
Generate the labeled and unlabeled datasets
Determining whether to stop choosing sample
the individualized binary logistic regression for categorical response...
the individualized binary logistic regression for ordinal response dat...
Print the results by the binary logistic regression model
Print the results by the generalized estimating equations.
Print the results by the multi-logistic regression model
Calculate quasi-likelihood under the independence model criterion (QIC...
The sequential logistic regression model for binary classification pro...
The sequential logistic regression model for multi-classification prob...
The The sequential method for generalized estimating equations case.
The sequential logistic regression model for multi-classification prob...
Add the new sample into labeled dataset from unlabeled dataset for the...
Add the new sample into labeled dataset from unlabeled dataset for the...
Sequential method to solve the the binary classification problem by Wang (2019) <arXiv:arXiv:1901.10079>, multi-class classification problem by Li (2020) <doi:10.1016/j.csda.2020.106911> and the highly stratified multiple-response problem by Chen (2019) <doi:10.1111/biom.13160>.