Bayesian Hierarchical Analysis of Cognitive Models of Choice

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Documentation for package ‘EMC2’ version 3.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

auto_thin	Automatically Thin an emc Object
auto_thin.emc	Automatically Thin an emc Object
chain_n	MCMC Chain Iterations
check	Convergence Checks for an emc Object
check.emc	Convergence Checks for an emc Object
compare	Information Criteria and Marginal Likelihoods
compare_subject	Information Criteria For Each Participant
contr.anova	Anova Style Contrast Matrix
contr.bayes	Contrast Enforcing Equal Prior Variance on each Level
contr.decreasing	Contrast Enforcing Decreasing Estimates
contr.increasing	Contrast Enforcing Increasing Estimates
credible	Posterior Credible Interval Tests
credible.emc	Posterior Credible Interval Tests
credint	Posterior Quantiles
credint.emc	Posterior Quantiles
credint.emc.prior	Posterior Quantiles
DDM	The Diffusion Decision Model
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_design	Get Design
get_design.emc	Get Design
get_design.emc.prior	Get Design
get_pars	Filter/Manipulate Parameters from emc Object
get_prior	Get Prior
get_prior.emc	Get Prior
hypothesis	Within-Model Hypothesis Testing
hypothesis.emc	Within-Model Hypothesis Testing
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_random_effects	Generate Subject-Level Parameters
mapped_pars	Parameter Mapping Back to the Design Factors
mapped_pars.emc	Parameter Mapping Back to the Design Factors
mapped_pars.emc.design	Parameter Mapping Back to the Design Factors
mapped_pars.emc.prior	Parameter Mapping Back to the Design Factors
merge_chains	Merge Samples
model_averaging	Model Averaging
pairs_posterior	Plot Within-Chain Correlations
parameters	Return Data Frame of Parameters
parameters.emc	Return Data Frame of Parameters
parameters.emc.prior	Return Data Frame of Parameters
plot.emc	Plot Function for emc Objects
plot.emc.design	Plot method for emc.design objects
plot.emc.prior	Plot a prior
plot_cdf	Plot Defective Cumulative Distribution Functions
plot_density	Plot Defective Densities
plot_design	Plot Design
plot_design.emc	Plot Design
plot_design.emc.design	Plot Design
plot_design.emc.prior	Plot Design
plot_pars	Plots Density for Parameters
plot_relations	Plot Group-Level Relations
plot_sbc_ecdf	Plot the ECDF Difference in SBC Ranks
plot_sbc_hist	Plot the Histogram of the Observed Rank Statistics of SBC
plot_stat	Plot Statistics on Data
predict.emc	Generate Posterior/Prior Predictives
predict.emc.prior	Generate Posterior/Prior Predictives
prior	Specify Priors for the Chosen Model
prior_help	Prior Specification Information
profile_plot	Likelihood Profile Plots
RDM	The Racing Diffusion Model
recovery	Recovery Plots
recovery.emc	Recovery Plots
run_bridge_sampling	Estimating Marginal Likelihoods Using WARP-III Bridge Sampling
run_emc	Custom Function for More Controlled Model Estimation
run_sbc	Simulation-Based Calibration
sampled_pars	Get Model Parameters from a Design
sampled_pars.emc	Get Model Parameters from a Design
sampled_pars.emc.design	Get Model Parameters from a Design
sampled_pars.emc.prior	Get Model Parameters from a Design
samples_LNR	LNR Model of Forstmann Data (First 3 Subjects)
subset.emc	Shorten an emc Object
summary.emc	Summary Statistics for emc Objects
summary.emc.design	Summary method for emc.design objects
summary.emc.prior	Summary method for emc.prior objects
update2version	Update EMC Objects to the Current Version