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 |