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YEAB

Yeab Ease the Analysis of Behavior (YEAB) is an R package that implements

  1. Several metrics from information theory as the Kullback-Leibler divergence and Mutual information, for discrete as well as continuous variables.
  2. Custom routines of Experimental Analysis of Behavior. For example, functions to process data from MED operant boxes.
  3. Several common analysis, like fitting hyperbolic and exponential models to delay discounting tasks, fitting the biexponential model to IRTs from variable interval schedules, etc.

Nota

Este paquete se desarrolló con presupuesto de la Convocatoria de Ciencia Básica y/o Ciencia de Frontera, Modalidad: Paradigmas y Controversias de la Ciencia 2022, con número de proyecto 320943 “APRENDIZAJE EN UNA TAREA DE ESTIMACIÓN TEMPORAL: EL PAPEL DE LA MAXIMIZACIÓN DE LA INFORMACI


For more information about how to install and use YEAB check our Wiki!

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Version

Install

install.packages('YEAB')

Monthly Downloads

258

Version

1.0.6

License

GPL (>= 3)

Maintainer

Emmanuel Alcala

Last Published

January 31st, 2025

Functions in YEAB (1.0.6)

eq_hyp

Hyperbolic function
fi60_raw_from_med

Raw Fixed Interval Data
dd_example

An example dataset of delays and normalized subjective values
exhaustive_sbp

Single breakpoint algorithm, the exhaustive version as the one used in Guilhardi & Church 2004
entropy_kde2d

Shannon entropy in two dimensions
hyp_data

Simulated Data for Hyperbolic Discounting
gauss_example_2

Gaussian Example 2 Data
val_in_interval

True value in interval
unit_normalization

Min-max normalization (also feature rescaling)
mut_info_knn

Mutual Information for Continuous Variables using kNN
gauss_example

Gaussian Example Data
n_between_intervals

Find maximum value within intervals
gaussian_fit

Gaussian + ramp fit with LM algorithm
hyp_data_list

Hypothetical dataset list for testing purposes
read_med

Process MED to csv based on standard data structure event.time
r_times

Reaction Times from Peak Procedure
gauss_example_1

Gaussian Example 1 Data
fleshler_hoffman

Fleshler & Hoffman (1962) progression
fwhm

Full Width at Half Maximum
exp_fit

Exponential fit with nls
get_bins

A function to binarize a numeric vector with a given resolution
objective_bp

Objective function for the breakpoint optimization algorithm
optimize_biexponential

Optimization Function for the Biexponential Model
gell_like

Gellerman-like series
sample_from_density

Sample from a density estimate
hyperbolic_fit

Hyperbolic fit with nls
ind_trials_obj_fun

Objective function for finding the best fit for individual trials
trapezoid_auc

Area under the curve (AUC)
mut_info_discrete

Mutual information of continuous variables using discretization
ind_trials_opt

Find the best fit for individual trials using optim
DD_data

Delay Discounting Data
berm

Biexponential Refractory Model (BERM)
KL_div

Computes the Kullback-Leibler divergence based on kernel density estimates
biexponential

Biexponential Model
curv_index_fry

Curvature index using Fry derivation
ceiling_multiple

Find the nearest multiple
bp_opt

Find the best fit for individual trials using optim
balci2019

Peak individual trial analysis using moving average
ab_range_normalization

Normalization (or rescaling) between arbitrary a and b
YEAB-package

YEAB: Analyze Data from Analysis of Behavior Experiments
f_table

Frequency table for binned data
curv_index_int

Curvature index by numerical integration
event_extractor

Event extractor
exhaustive_lhl

Individual trial analysis for peak procedure data