| bistablehistory-package | Cumulative History Analysis for Bistable Perception Time Series |
| bayes_R2 | Computes R-squared using Bayesian R-squared approach. |
| bayes_R2.cumhist | Computes R-squared using Bayesian R-squared approach. |
| bistablehistory | Cumulative History Analysis for Bistable Perception Time Series |
| br | Binocular rivalry data |
| br_contrast | Binocular rivalry, variable contrast |
| br_singleblock | Single run for binocular rivalry stimulus |
| br_single_subject | Single experimental session for binocular rivalry stimulus |
| coef.cumhist | Extract Model Coefficients |
| compute_history | Computes cumulative history for the time-series |
| cumhist | Class 'cumhist'. |
| cumhist-class | Class 'cumhist'. |
| extract_history | Computes history for a fitted model |
| extract_history_parameter | Extracts a history parameter as a matrix |
| extract_replicate_term_to_matrix | Extract a term and replicates it randomN times for each linear model |
| extract_term_to_matrix | Extracts a term with one column per fixed or random-level into a matrix |
| fast_history_compute | Computes cumulative history |
| fit_cumhist | Fits cumulative history for bistable perceptual rivalry displays. |
| fixef | Extract the fixed-effects estimates |
| historyef | Extract the history-effects estimates |
| history_mixed_state | Extract values of used or fitted history parameter mixed_state |
| history_parameter | Extract values of used or fitted history parameter |
| history_tau | Extract values of used or fitted history parameter tau |
| kde | Kinetic-depth effect data |
| kde_two_observers | Multirun data for two participants, kinetic-depth effect display |
| loo.cumhist | Computes an efficient approximate leave-one-out cross-validation via loo library. It can be used for a model comparison via loo::loo_compare() function. |
| nc | Necker cube data |
| predict.cumhist | Computes predicted dominance phase durations using posterior predictive distribution. |
| predict_history | Computes predicted cumulative history using posterior predictive distribution. |
| predict_samples | Computes prediction for a each sample. |
| preprocess_data | Preprocesses time-series data for fitting |
| print.cumhist | Prints out cumhist object |
| summary.cumhist | Summary for a cumhist object |
| waic.cumhist | Computes widely applicable information criterion (WAIC). |
| _PACKAGE | Cumulative History Analysis for Bistable Perception Time Series |