Man pages for EMC2
Bayesian Hierarchical Analysis of Cognitive Models of Choice
| align_loadings | Reorder MCMC Samples of Factor Loadings |
| auto_thin | Automatically Thin an emc Object |
| chain_n | MCMC Chain Iterations |
| check | 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 |
| credint | Posterior Quantiles |
| cut_factors | Cut Factors Based on Credible Loadings |
| 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 |
| EMC2-package | EMC2: Bayesian Hierarchical Analysis of Cognitive Models of... |
| ess_summary | Effective Sample Size |
| factor_diagram | Factor diagram plot #Makes a factor diagram plot. Heavily... |
| fit | Model Estimation in EMC2 |
| forstmann | Forstmann et al.'s Data |
| gd_summary | Gelman-Rubin Statistic |
| get_BayesFactor | Bayes Factors |
| get_data | Get Data |
| get_design | Get Design |
| get_group_design | Get Group Design |
| get_pars | Filter/Manipulate Parameters from emc Object |
| get_prior | Get Prior |
| get_trend_pnames | Get parameter types from trend object |
| group_design | Create Group-Level Design Matrices |
| high_pass_filter | Apply High-Pass Filtering to fMRI Data |
| hypothesis | 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 |
| 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 |
| 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 |
| pairs_posterior | Plot Within-Chain Correlations |
| parameters | Return Data Frame of Parameters |
| 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_fmri | Plot fMRI Design Matrix |
| plot.emc | Plot Function for emc Objects |
| plot.emc.design | Plot method for emc.design objects |
| plot.emc.prior | Plot a prior |
| 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 |
| 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 |
| 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... |
| run_emc | Fine-Tuned Model Estimation |
| run_hyper | Run a Group-level Model. |
| run_sbc | Simulation-Based Calibration |
| sampled_pars | 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 |
| trend_help | Get help information for trend kernels and bases |
| update2version | Update EMC Objects to the Current Version |
