Function reference • bistablehistory

All functions

bayes_R2(<cumhist>): Computes R-squared using Bayesian R-squared approach.

bistablehistory-package 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: 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).