alt_delta | Rescorla-Wagner (Delta) Model |
alt_gamma | Rescorla-Wagner (Gamma) Model |
bandit2arm_delta | Rescorla-Wagner (Delta) Model |
bandit4arm2_kalman_filter | Kalman Filter |
bandit4arm_2par_lapse | 3 Parameter Model, without C (choice perseveration), R... |
bandit4arm_4par | 4 Parameter Model, without C (choice perseveration) |
bandit4arm_lapse | 5 Parameter Model, without C (choice perseveration) but with... |
bandit4arm_lapse_decay | 5 Parameter Model, without C (choice perseveration) but with... |
bandit4arm_singleA_lapse | 4 Parameter Model, without C (choice perseveration) but with... |
banditNarm_2par_lapse | 3 Parameter Model, without C (choice perseveration), R... |
banditNarm_4par | 4 Parameter Model, without C (choice perseveration) |
banditNarm_delta | Rescorla-Wagner (Delta) Model |
banditNarm_kalman_filter | Kalman Filter |
banditNarm_lapse | 5 Parameter Model, without C (choice perseveration) but with... |
banditNarm_lapse_decay | 5 Parameter Model, without C (choice perseveration) but with... |
banditNarm_singleA_lapse | 4 Parameter Model, without C (choice perseveration) but with... |
bart_ewmv | Exponential-Weight Mean-Variance Model |
bart_par4 | Re-parameterized version of BART model with 4 parameters |
cgt_cm | Cumulative Model |
choiceRT_ddm | Drift Diffusion Model |
choiceRT_ddm_single | Drift Diffusion Model |
choiceRT_lba | Choice Reaction Time task, linear ballistic accumulator... |
choiceRT_lba_single | Choice Reaction Time task, linear ballistic accumulator... |
cra_exp | Exponential Subjective Value Model |
cra_linear | Linear Subjective Value Model |
dbdm_prob_weight | Probability Weight Function |
dd_cs | Constant-Sensitivity (CS) Model |
dd_cs_single | Constant-Sensitivity (CS) Model |
dd_exp | Exponential Model |
dd_hyperbolic | Hyperbolic Model |
dd_hyperbolic_single | Hyperbolic Model |
estimate_mode | Function to estimate mode of MCMC samples |
extract_ic | Extract Model Comparison Estimates |
gng_m1 | RW + noise |
gng_m2 | RW + noise + bias |
gng_m3 | RW + noise + bias + pi |
gng_m4 | RW (rew/pun) + noise + bias + pi |
hBayesDM_model | hBayesDM Model Base Function |
hBayesDM-package | Hierarchical Bayesian Modeling of Decision-Making Tasks |
HDIofMCMC | Compute Highest-Density Interval |
igt_orl | Outcome-Representation Learning Model |
igt_pvl_decay | Prospect Valence Learning (PVL) Decay-RI |
igt_pvl_delta | Prospect Valence Learning (PVL) Delta |
igt_vpp | Value-Plus-Perseverance |
multiplot | Function to plot multiple figures |
peer_ocu | Other-Conferred Utility (OCU) Model |
plotDist | Plots the histogram of MCMC samples. |
plot.hBayesDM | General Purpose Plotting for hBayesDM. This function plots... |
plotHDI | Plots highest density interval (HDI) from (MCMC) samples and... |
plotInd | Plots individual posterior distributions, using the stan_plot... |
printFit | Print model-fits (mean LOOIC or WAIC values in addition to... |
prl_ewa | Experience-Weighted Attraction Model |
prl_fictitious | Fictitious Update Model |
prl_fictitious_multipleB | Fictitious Update Model |
prl_fictitious_rp | Fictitious Update Model, with separate learning rates for... |
prl_fictitious_rp_woa | Fictitious Update Model, with separate learning rates for... |
prl_fictitious_woa | Fictitious Update Model, without alpha (indecision point) |
prl_rp | Reward-Punishment Model |
prl_rp_multipleB | Reward-Punishment Model |
pst_gainloss_Q | Gain-Loss Q Learning Model |
pst_Q | Q Learning Model |
pstRT_ddm | Drift Diffusion Model |
pstRT_rlddm1 | Reinforcement Learning Drift Diffusion Model 1 |
pstRT_rlddm6 | Reinforcement Learning Drift Diffusion Model 6 |
ra_noLA | Prospect Theory, without loss aversion (LA) parameter |
ra_noRA | Prospect Theory, without risk aversion (RA) parameter |
ra_prospect | Prospect Theory |
rdt_happiness | Happiness Computational Model |
rhat | Function for extracting Rhat values from an hBayesDM object |
task2AFC_sdt | Signal detection theory model |
ts_par4 | Hybrid Model, with 4 parameters |
ts_par6 | Hybrid Model, with 6 parameters |
ts_par7 | Hybrid Model, with 7 parameters (original model) |
ug_bayes | Ideal Observer Model |
ug_delta | Rescorla-Wagner (Delta) Model |
wcs_sql | Sequential Learning Model |
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