Bayesian Hierarchical Analysis of Cognitive Models of Choice


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Documentation for package ‘EMC2’ version 3.1.0

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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