Cumulative History Analysis for Bistable Perception Time Series


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Documentation for package ‘bistablehistory’ version 1.1.1

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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).