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hBayesDM (version 0.4.0)

Hierarchical Bayesian Modeling of Decision-Making Tasks

Description

Fit an array of decision-making tasks with computational models in a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis of various computational models with a single line of coding.

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Version

Install

install.packages('hBayesDM')

Monthly Downloads

494

Version

0.4.0

License

GPL-3

Maintainer

Woo-Young Ahn

Last Published

May 23rd, 2017

Functions in hBayesDM (0.4.0)

HDIofMCMC

Compute Highest-Density Interval
bandit2arm_delta

Two-Arm Bandit Task
dd_cs

Delay Discounting Task
choiceRT_ddm

Choice Reaction Time task, drift diffusion modeling
bandit4arm_4par

4-armed bandit task
bandit4arm_lapse

4-armed bandit task
choiceRT_lba

Choice Reaction Time task, linear ballistic accumulator modeling
choiceRT_lba_single

Choice Reaction Time task, linear ballistic accumulator modeling
dd_cs_single

Delay Discounting Task (Ebert & Prelec, 2007)
dd_hyperbolic_single

Delay Discounting Task (Ebert & Prelec, 2007)
estimate_mode

Function to estimate mode of MCMC samples
extract_ic

Extract Model Comparison Estimates
choiceRT_ddm_single

Choice Reaction Time task, drift diffusion modeling
igt_pvl_decay

Iowa Gambling Task
igt_pvl_delta

Iowa Gambling Task (Ahn et al., 2008)
gng_m2

Orthogonalized Go/Nogo Task
gng_m3

Orthogonalized Go/Nogo Task
plotHDI

Plots highest density interval (HDI) from (MCMC) samples and prints HDI in the R console. HDI is indicated by a red line.
gng_m4

Orthogonalized Go/Nogo Task
hBayesDM-package

Hierarchical Bayesian Modeling of Decision-Making Tasks
ug_bayes

Norm-Training Ultimatum Game
ug_delta

Norm-Training Ultimatum Game
gng_m1

Orthogonalized Go/Nogo Task
plot.hBayesDM

General Purpose Plotting for hBayesDM. This function plots hyper parameters.
plotDist

Plots the histogram of MCMC samples.
prl_fictitious

Probabilistic Reversal Learning Task
dd_exp

Delay Discounting Task
dd_hyperbolic

Delay Discounting Task
printFit

Print model-fits (mean LOOIC and WAIC values) of hBayesDM Models
prl_ewa

Probabilistic Reversal Learning Task
prl_fictitious_multipleB

Probabilistic Reversal Learning Task (Glascher et al, 2009), multiple blocks per subject
plotInd

Plots individual posterior distributions, using the stan_plot function of the rstan package
ra_noLA

Risk Aversion Task
ra_noRA

Risk Aversion Task
igt_vpp

Iowa Gambling Task
multiplot

Function to plot multiple figures
prl_rp

Probabilistic Reversal Learning Task
prl_rp_multipleB

Probabilistic Reversal Learning Task, multiple blocks per subject
ra_prospect

Risk Aversion Task
rhat

Function for extracting Rhat values from an hBayesDM object