Bayesian Hierarchical Analysis of Cognitive Models of Choice

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Documentation for package ‘EMC2’ version 2.0.2

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add_constants Augments parameter matrix or vector p with constant parameters (also used in data)
auto_burn Runs burn-in for emc.
chain_n chain_n()
check Convergence checks for an emc object
check.emc Convergence checks for an emc object
compare Information criteria and marginal likelihoods
compare_MLL Calculate a table of model probabilities based for a list of samples objects based on samples of marginal log-likelihood (MLL) added to these objects by run_IS2. Probabilities estimated by a bootstrap ath picks a vector of MLLs, one for each model in the list randomly with replacement nboot times, calculates model probabilities and averages
compare_subject Information criteria for each participant
contr.anova Anova style contrast matrix
contr.bayes Contrast to enforce equal prior variance on each level
contr.decreasing Contrast to enforce decreasing estimates
contr.increasing Contrast to enforce increasing estimates
credible Posterior credible interval tests
credible.emc Posterior credible interval tests
DDM The Diffusion Decision Model
DDMt0natural Diffusion decision model with t0 on the natural scale
design Specify a design and model
ess_summary Effective sample size
ess_summary.emc Effective sample size
fit Model estimation in EMC2
fit.emc Model estimation in EMC2
forstmann Forstmann et al.'s data
gd_summary Gelman-Rubin statistic
gd_summary.emc Gelman-Rubin statistic
get_BayesFactor Bayes Factors
get_data Get data
get_data.emc Get data
get_pars Filter/manipulate parameters from emc object
get_prior_blocked Prior specification or prior sampling for blocked estimation
get_prior_diag Prior specification or prior sampling for diagonal estimation
get_prior_factor Prior specification and prior sampling for factor estimation
get_prior_SEM Prior specification or prior sampling for SEM estimation.
get_prior_single Prior specification or prior sampling for single subject estimation
get_prior_standard Prior specification or prior sampling for standard estimation.
hypothesis Within-model hypothesis testing
hypothesis.emc Within-model hypothesis testing
IC Calculate information criteria (DIC, BPIC), effective number of parameters and constituent posterior deviance (D) summaries (meanD = mean of D, Dmean = D for mean of posterior parameters and minD = minimum of D).
init_chains Initialize chains
LBA The Linear Ballistic Accumulator model
LNR The Log-Normal Race Model
make_data Simulate data
make_emc Make an emc object
make_factor_diagram Factor diagram plot
make_missing make_missing
make_random_effects Make random effects
mapped_par Parameter mapping back to the design factors
merge_chains Merge samples
pairs_posterior Plot within-chain correlations
parameters Returns a parameter type from an emc object as a data frame.
parameters.emc Returns a parameter type from an emc object as a data frame.
plot.emc Plot function for emc objects
plot_defective_density Plot defective densities for each subject and cell
plot_fit Posterior predictive checks
plot_fit_choice Plots choice data
plot_mcmc Plot MCMC
plot_mcmc_list Plot MCMC.list
plot_pars Plots density for parameters
plot_prior Title
plot_relations Plot relations
posterior_summary Posterior quantiles
posterior_summary.emc Posterior quantiles
predict.emc Generate posterior predictives
prior Prior specification
probit Gaussian Signal Detection Theory Model
profile_plot Likelihood profile plots
RDM The Racing Diffusion Model
recovery Recovery plots
recovery.emc Recovery plots
run_adapt Runs adapt stage for emc.
run_bridge_sampling Estimating Marginal likelihoods using WARP-III bridge sampling
run_emc Custom function for more controlled model estimation
run_IS2 Runs IS2 from Tran et al. 2021 on a list of emc
run_sample Runs sample stage for emc.
sampled_p_vector Get model parameters from a design
samples_LNR An emc object of an LNR model of the Forstmann dataset using the first three subjects
standardize_loadings Standardized factor loadings
subset.emc Shorten an emc object
summary.emc Summary statistics for emc objects