Package: YEAB 1.0.6

Emmanuel Alcala

YEAB: Analyze Data from Analysis of Behavior Experiments

Analyze data from behavioral experiments conducted using 'MED-PC' software developed by Med Associates Inc. Includes functions to fit exponential and hyperbolic models for delay discounting tasks, exponential mixtures for inter-response times, and Gaussian plus ramp models for peak procedure data, among others. For more details, refer to Alcala et al. (2023) <doi:10.31234/osf.io/8aq2j>.

Authors:Emmanuel Alcala [aut, cre], Rodrigo Sosa [aut], Victor Reyes [aut]

YEAB_1.0.6.tar.gz
YEAB_1.0.6.tar.gz(r-4.5-noble)YEAB_1.0.6.tar.gz(r-4.4-noble)
YEAB_1.0.6.tgz(r-4.4-emscripten)YEAB_1.0.6.tgz(r-4.3-emscripten)
YEAB.pdf |YEAB.html
YEAB/json (API)
NEWS

# Install 'YEAB' in R:
install.packages('YEAB', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.00 score 33 exports 77 dependencies

Last updated 15 days agofrom:02597706a8. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 01 2025
R-4.5-linuxOKFeb 01 2025

Exports:ab_range_normalizationbalci2019bermbiexponentialbp_optceiling_multiplecurv_index_frycurv_index_intentropy_kde2deq_hypevent_extractorexhaustive_lhlexhaustive_sbpexp_fitf_tablefleshler_hoffmanfwhmgaussian_fitgell_likeget_binshyperbolic_fitind_trials_optKL_divmut_info_discretemut_info_knnn_between_intervalsobjective_bpoptimize_bermread_medsample_from_densitytrapezoid_aucunit_normalizationval_in_interval

Dependencies:askpassbootclicliprclustercodetoolscolorspacecrayoncredentialscurldata.tabledescdoParalleldplyrfansifarverFNNforeachfsgenericsgertggplot2ghgitcredsgluegridExtragtablehttr2infotheoiniisobanditeratorsjsonlitekernlabKernSmoothkslabelinglatticelifecyclemagrittrMASSMatrixmclustmgcvminpack.lmmulticoolmunsellmvtnormnlmeopensslpillarpkgconfigPolychromepracmapurrrR6rappdirsRColorBrewerRcpprlangrprojrootrstudioapiscalesscatterplot3dsfsmiscsystibbletidyselectusethisutf8vctrsviridisLitewhiskerwithryamlzipzoo

balci2019()

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biexponential() & berm()

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breakpoint()

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curv_indexes()

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delay_discounting_fit()

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entropy_kde2d()

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event_extractor()

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f_table()

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fleshler_hoffman()

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fwhm()

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gaussian_fit()

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gell_like()

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get_bins()

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ind_trails_opt()

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KL_div()

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mut_info()

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read_med()

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val_in_interval()

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sample_from_density()

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unit_normalization()

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Readme and manuals

Help Manual

Help pageTopics
Normalization (or rescaling) between arbitrary a and bab_range_normalization
Peak individual trial analysis using moving averagebalci2019
Biexponential Refractory Model (BERM)berm berm_log_likelihood map_onto optimize_berm param_conver
Biexponential Modelbiexponential
Find the best fit for individual trials using 'optim'bp_opt
Find the nearest multipleceiling_multiple
Curvature index using Fry derivationcurv_index_fry
Curvature index by numerical integrationcurv_index_int
Delay Discounting DataDD_data
An example dataset of delays and normalized subjective valuesdd_example
Shannon entropy in two dimensionsentropy_kde2d
Hyperbolic functioneq_hyp
Event extractorevent_extractor
Individual trial analysis for peak procedure dataexhaustive_lhl
Single breakpoint algorithm, the exhaustive version as the one used in Guilhardi & Church 2004exhaustive_sbp
Exponential fit with nlsexp_fit
Frequency table for binned dataf_table
Raw Fixed Interval Datafi60_raw_from_med
Fleshler & Hoffman (1962) progressionfleshler_hoffman
Full Width at Half Maximumfwhm
Gaussian Example Datagauss_example
Gaussian Example 1 Datagauss_example_1
Gaussian Example 2 Datagauss_example_2
Gaussian + ramp fit with LM algorithmgaussian_fit
Gellerman-like seriesgell_like
A function to binarize a numeric vector with a given resolutionget_bins
Simulated Data for Hyperbolic Discountinghyp_data
Hypothetical dataset list for testing purposeshyp_data_list
Hyperbolic fit with nlshyperbolic_fit
Objective function for finding the best fit for individual trialsind_trials_obj_fun
Find the best fit for individual trials using 'optim'ind_trials_opt
Computes the Kullback-Leibler divergence based on kernel density estimatesKL_div
Mutual information of continuous variables using discretizationmut_info_discrete
Mutual Information for Continuous Variables using kNNmut_info_knn
Find maximum value within intervalsn_between_intervals
Objective function for the breakpoint optimization algorithmobjective_bp
Optimization Function for the Biexponential Modelbiexponential_log_likelihood optimize_biexponential
Reaction Times from Peak Procedurer_times
Process MED to csv based on standard data structure event.timeread_med
Sample from a density estimatesample_from_density
Area under the curve (AUC)trapezoid_auc
Min-max normalization (also feature rescaling)unit_normalization
True value in intervalval_in_interval