align_loadings | Reorder MCMC Samples of Factor Loadings |
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 |
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 |
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 |
ess_summary | Effective Sample Size |
ess_summary.emc | Effective Sample Size |
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 |
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 |
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 |
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 |
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 |
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_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_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 |
reshape_events | Reshape events data for fMRI analysis |
run_bridge_sampling | Estimating Marginal Likelihoods Using WARP-III Bridge Sampling |
run_emc | Fine-Tuned 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.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.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 |