Man pages for hmcdm
Hidden Markov Cognitive Diagnosis Models for Learning
| Design_array | Design array |
| ETAmat | Generate ideal response matrix |
| hmcdm | Gibbs sampler for learning models |
| hmcdm-package | hmcdm: Hidden Markov Cognitive Diagnosis Models for Learning |
| inv_bijectionvector | Convert integer to attribute pattern |
| L_real_array | Observed response times array |
| OddsRatio | Compute item pairwise odds ratio |
| pp_check.hmcdm | Graphical posterior predictive checks for hidden Markov... |
| Q_list_g | Generate a list of Q-matrices for each examinee. |
| Q_matrix | Q-matrix |
| random_Q | Generate random Q matrix |
| rOmega | Generate a random transition matrix for the first order... |
| sim_alphas | Generate attribute trajectories under the specified hidden... |
| sim_hmcdm | Simulate responses from the specified model (entire cube) |
| sim_RT | Simulate item response times based on Wang et al.'s (2018)... |
| summary.hmcdm | Summarizing Hidden Markov Cognitive Diagnosis Model Fits |
| Test_order | Test block ordering of each test version |
| Test_versions | Subjects' test version |
| TPmat | Generate monotonicity matrix |
| Y_real_array | Observed response accuracy array |
