# Bayesian Hierarchical Analysis of Cognitive Models of Choice

## Documentation for package ‘EMC2’ version 3.3.0

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

## Help Pages

A C D E F G H I L M P R S T U

## -- A --

align_loadings | Reorder MCMC Samples of Factor Loadings
auto_thin | Automatically Thin an emc Object
auto_thin.emc | Automatically Thin an emc Object

## -- C --

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
convolve_design_matrix | Convolve Events with HRF to Construct Design Matrices
credible | Posterior Credible Interval Tests
credible.emc | Posterior Credible Interval Tests
credint | Posterior Quantiles
credint.emc | Posterior Quantiles
credint.emc.prior | Posterior Quantiles
cut_factors | Cut Factors Based on Credible Loadings

## -- D --

DDM | The Diffusion Decision Model
DDMGNG | The GNG (go/nogo) Diffusion Decision Model
design | Specify a Design and Model
design_fmri | Create fMRI Design for EMC2 Sampling

## -- E --

ess_summary | Effective Sample Size
ess_summary.emc | Effective Sample Size

## -- F --

factor_diagram | Factor diagram plot #Makes a factor diagram plot. Heavily based on the fa.diagram function of the 'psych' package.
fit | Model Estimation in EMC2
fit.emc | Model Estimation in EMC2
forstmann | Forstmann et al.'s Data

## -- G --

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_group_design | Get Group Design
get_group_design.emc | Get Group Design
get_group_design.emc.prior | Get Group Design
get_pars | Filter/Manipulate Parameters from emc Object
get_prior | Get Prior
get_prior.emc | Get Prior
get_trend_pnames | Get parameter types from trend object
group_design | Create Group-Level Design Matrices

## -- H --

high_pass_filter | Apply High-Pass Filtering to fMRI Data
hypothesis | Within-Model Hypothesis Testing
hypothesis.emc | Within-Model Hypothesis Testing

## -- I --

init_chains | Initialize Chains

## -- L --

LBA | The Linear Ballistic Accumulator model
LNR | The Log-Normal Race Model

## -- M --

make_data | Simulate Data
make_emc | Make an emc Object
make_random_effects | Generate Subject-Level Parameters
make_SEM_diagram | Make SEM Diagram
make_sem_structure | Define Structural Equation Model (SEM) Matrices
make_trend | Create a trend specification for model 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
MRI | GLM model for fMRI data
MRI_AR1 | Create an AR(1) GLM model for fMRI data

## -- P --

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_caf | Plot conditional accuracy functions
plot_cdf | Plot Defective Cumulative Distribution Functions
plot_delta | Plot Difference of 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_design_fmri | Plot fMRI Design Matrix
plot_fmri | Plot fMRI peri-stimulus time courses
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_ss_if | Plot Inhibition Functions
plot_ss_srrt | Plot Mean SRRT
plot_stat | Plot Statistics on Data
plot_trend | Plots trends over time
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

## -- R --

RDM | The Racing Diffusion Model
recovery | Recovery Plots
recovery.emc | Recovery Plots
register_trend | Register a custom C++ trend kernel
reshape_events | Reshape events data for fMRI analysis
rotate_loadings | Rotate loadings based on posterior median
run_bridge_sampling | Estimating Marginal Likelihoods Using WARP-III Bridge Sampling
run_emc | Fine-Tuned Model Estimation
run_hyper | Run a Group-level Model.
run_sbc | Simulation-Based Calibration

## -- S --

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.group_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)
SDT | Gaussian Signal Detection Theory Model for Binary Responses
split_timeseries | Split fMRI Timeseries Data by ROI Columns
subset.emc | Shorten an emc Object
summary.emc | Summary Statistics for emc Objects
summary.emc.design | Summary method for emc.design objects
summary.emc.group_design | Summary method for emc.group_design objects
summary.emc.prior | Summary method for emc.prior objects

## -- T --

trend_help | Get help information for trend kernels and bases

## -- U --

update2version | Update EMC Objects to the Current Version