Man pages for LucasKookUZH/ontram-pkg
Ordinal transformation model neural networks
| apply_gradient | Compute gradient contribution for exact response |
| apply_gradient2 | Compute gradient contribution for exact response |
| coef.k_ontram | S3 methods for 'k_ontram' |
| coef.ontram | Function for coef for simple ontram |
| compute_kappa | compute Cohen's weighted kappa |
| compute_logLik | Compute logLik contributions for exact response |
| compute_logLik2 | Compute logLik contributions for exact response |
| dot-initializer_bias_gamma | initializer for equal class probs |
| dot-to_gamma | theta to gamma |
| dot-to_theta | gamma to theta |
| eval_batchwise | Evaluate fitted ontram models |
| expected_score | Expected weighted kappa score |
| fit_k_ontram | Function for estimating a 'k_ontram' or 'k_ontram_ci' model |
| fit_k_ontram_augmented_data | Function for estimating a 'k_ontram' or 'k_ontram_ci' model... |
| fit_ontram | Function for estimating the model |
| fit_ontram2 | Function for estimating the model |
| fit_ontram3 | Function for estimating the model |
| gamma_to_theta | Transform raw intercept function to constrained one |
| get_expected | expected number of agreements under independence |
| get_loss | get kappa loss python function |
| get_metric | get kappa metric python function |
| get_weights_by_name | Get weights by name of layer |
| kappa_loss | Weighted kappa loss function (R) |
| k_mod_baseline | Baseline model |
| k_ontram | Keras interface to ONTRAMs |
| k_ontram_acc | Accuracy function |
| k_ontram_auc | AUC function |
| k_ontram_binll | Binary logLik function |
| k_ontram_cqwk | Continuous qwk |
| k_ontram_loss | Another keras implementation of the ontram loss |
| k_ontram_qwk | Discrete qwk |
| k_ontram_rps | RPS loss |
| layer_trafo_intercept | Layer for transforming raw intercepts using softplus function |
| load_model_ontram | Load ontram model |
| load_ontram_history | Save ontram history |
| metric_acc | Accuracy metric |
| metric_binll | Binary NLL metric |
| metric_cqwk | Continuous qwk metric |
| metric_k_auc | Accuracy metric |
| metric_nll | NLL metric |
| metric_qwk | Discrete qwk metric |
| metric_rps | CRPS metric |
| mod_baseline | Sequential model for the intercept function |
| mod_shift | Sequential model for the shift function |
| mod_weights.ontram | Extract model weights |
| ontram | General ordinal transformation neural network |
| ontram_polr | Combine intercept and tabular model |
| pgompertz | Gompertz cdf python function |
| pgumbel | Gumbel cdf python function |
| plot.ontram_history | Plot ontram history |
| predict.k_ontram | S3 methods for 'k_ontram' |
| predict.ontram | Function for predicting cdf, pdf and class and compute logLik |
| predict.ontram_rv | Function for predicting cdf, pdf and class and compute logLik |
| rps | RPS with weights |
| save_k_hist | Save history of keras model |
| save_model_ontram | Save ontram model |
| save_ontram_history | Save ontram history |
| simulate.k_ontram | Simulate Responses |
| simulate.ontram | Simulate Responses |
| warmstart.k_ontram | Set initial weights |
| warmstart.k_ontram_ci | Set initial weights |
| warmstart.ontram | Set initial weights |
| warmstart.ontram_rv | Set initial weights |
| weight_scheme | Weighting scheme for Cohen's kappa |
