hBayesDM/R/DESCRIPTION at develop · mkdir-eherms/hBayesDM · GitHub

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Package: hBayesDM
Title: Hierarchical Bayesian Modeling of Decision-Making Tasks
Version: 1.3.0.9000
Date: 2022-09-13
Author:
    Woo-Young Ahn [aut, cre],
    Nate Haines [aut],
    Lei Zhang [aut],
    Harhim Park [ctb],
    Jaeyeong Yang [ctb],
    Jethro Lee [ctb]
Authors@R: c(
    person("Woo-Young", "Ahn", email = "wooyoung.ahn@gmail.com", role = c("aut", "cre")),
    person("Nate", "Haines", email = "haines.175@osu.edu", role = c("aut")),
    person("Lei", "Zhang", email = "bnuzhanglei2008@gmail.com", role = c("aut")),
    person("Harhim", "Park", email = "hrpark12@gmail.com", role = c("ctb")),
    person("Jaeyeong", "Yang", email = "jaeyeong.yang1125@gmail.com", role = c("ctb")),
    person("Jethro", "Lee", email = "dlemfh96@snu.ac.kr", role = c("ctb")))
Maintainer: Woo-Young Ahn <wooyoung.ahn@gmail.com>
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
    (Ahn et al., 2017) <doi:10.1162/CPSY_a_00002>.
Depends:
    R (>= 3.4.0),
    Rcpp (>= 0.12.0),
    methods
Imports:
    rstan (>= 2.18.1),
    loo (>= 2.0),
    grid,
    parallel,
    ggplot2,
    data.table
LinkingTo:
    BH (>= 1.66.0),
    Rcpp (>= 0.12.0),
    RcppEigen (>= 0.3.3.3.0),
    rstan (>= 2.18.1),
    StanHeaders (>= 2.18.0)
URL: https://github.com/CCS-Lab/hBayesDM
BugReports: https://github.com/CCS-Lab/hBayesDM/issues
License: GPL-3
NeedsCompilation: yes
Encoding: UTF-8
RoxygenNote: 7.2.1
SystemRequirements: GNU make
Collate:
    'HDIofMCMC.R'
    'preprocess_funcs.R'
    'stanmodels.R'
    'settings.R'
    'hBayesDM_model.R'
    'alt_delta.R'
    'alt_gamma.R'
    'bandit2arm_delta.R'
    'bandit4arm2_kalman_filter.R'
    'bandit4arm_2par_lapse.R'
    'bandit4arm_4par.R'
    'bandit4arm_lapse.R'
    'bandit4arm_lapse_decay.R'
    'bandit4arm_singleA_lapse.R'
    'banditNarm_2par_lapse.R'
    'banditNarm_4par.R'
    'banditNarm_delta.R'
    'banditNarm_kalman_filter.R'
    'banditNarm_lapse.R'
    'banditNarm_lapse_decay.R'
    'banditNarm_singleA_lapse.R'
    'bart_ewmv.R'
    'bart_par4.R'
    'cgt_cm.R'
    'choiceRT_ddm.R'
    'choiceRT_ddm_single.R'
    'choiceRT_lba.R'
    'choiceRT_lba_single.R'
    'cra_exp.R'
    'cra_linear.R'
    'dbdm_prob_weight.R'
    'dd_cs.R'
    'dd_cs_single.R'
    'dd_exp.R'
    'dd_hyperbolic.R'
    'dd_hyperbolic_single.R'
    'estimate_mode.R'
    'extract_ic.R'
    'gng_m1.R'
    'gng_m2.R'
    'gng_m3.R'
    'gng_m4.R'
    'hBayesDM.R'
    'igt_orl.R'
    'igt_pvl_decay.R'
    'igt_pvl_delta.R'
    'igt_vpp.R'
    'multiplot.R'
    'peer_ocu.R'
    'plot.hBayesDM.R'
    'plotDist.R'
    'plotHDI.R'
    'plotInd.R'
    'printFit.R'
    'prl_ewa.R'
    'prl_fictitious.R'
    'prl_fictitious_multipleB.R'
    'prl_fictitious_rp.R'
    'prl_fictitious_rp_woa.R'
    'prl_fictitious_woa.R'
    'prl_rp.R'
    'prl_rp_multipleB.R'
    'pstRT_ddm.R'
    'pstRT_rlddm1.R'
    'pstRT_rlddm6.R'
    'pst_Q.R'
    'pst_gainloss_Q.R'
    'ra_noLA.R'
    'ra_noRA.R'
    'ra_prospect.R'
    'rdt_happiness.R'
    'rhat.R'
    'task2AFC_sdt.R'
    'ts_par4.R'
    'ts_par6.R'
    'ts_par7.R'
    'ug_bayes.R'
    'ug_delta.R'
    'wcs_sql.R'
    'zzz.R'
Suggests:
    testthat