Man pages for seqest
Sequential Method for Classification and Generalized Estimating Equations Problem

A_optimal_catGet the most informative subjects from unlabeled dataset for...
A_optimal_ordGet the most informative subjects from unlabeled dataset for...
ase_seq_logitvariable selection and stopping criterion
D_optimalGet the most informative subjects for the clustered data
evaluateGEEModelThe adaptive shrinkage estimate for generalized estimating...
genBinGenerate the correlated binary response data for discrete...
gen_bin_datagenerate the data used for the model experiment
genCorMatGenerate the correlation matrix for the clusteded data
gen_GEE_dataGenerate the datasets with clusters
gen_multi_dataGenerate the training data and testing data for the...
getMHGet the matrices M and H for the clustered data for the GEE...
getWHGet the matrices W and H for the categorical case
getWH_ordGet the matrices W and H for the ordinal case
init_multi_dataGenerate the labeled and unlabeled datasets
is_stop_ASEDetermining whether to stop choosing sample
logit_modelthe individualized binary logistic regression for categorical...
logit_model_ordthe individualized binary logistic regression for ordinal...
print.seqbinPrint the results by the binary logistic regression model
print.seqGEEPrint the results by the generalized estimating equations.
print.seqmultiPrint the results by the multi-logistic regression model
QICCalculate quasi-likelihood under the independence model...
seq_bin_modelThe sequential logistic regression model for binary...
seq_cat_modelThe sequential logistic regression model for...
seq_GEE_modelThe The sequential method for generalized estimating...
seq_ord_modelThe sequential logistic regression model for...
update_data_catAdd the new sample into labeled dataset from unlabeled...
update_data_ordAdd the new sample into labeled dataset from unlabeled...
seqest documentation built on July 2, 2020, 2:28 a.m.