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 |