chain_n | chain_n() |
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 to enforce equal prior variance on each level |
contr.decreasing | Contrast to enforce decreasing estimates |
contr.increasing | Contrast to enforce increasing estimates |
credible | Posterior credible interval tests |
credible.emc | Posterior credible interval tests |
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_pars | Filter/manipulate parameters from emc object |
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 | Make random effects |
mapped_par | Parameter mapping back to the design factors |
merge_chains | Merge samples |
pairs_posterior | Plot within-chain correlations |
parameters | Returns a parameter type from an emc object as a data frame. |
parameters.emc | Returns a parameter type from an emc object as a data frame. |
plot.emc | Plot function for emc objects |
plot_defective_density | Plot defective densities for each subject and cell |
plot_fit | Posterior predictive checks |
plot_pars | Plots density for parameters |
plot_prior | Title |
plot_relations | Plot relations |
plot_sbc_ecdf | Plot the ECDF difference in SBC ranks |
plot_sbc_hist | Plot the histogram of the observed rank statistics of SBC |
posterior_summary | Posterior quantiles |
posterior_summary.emc | Posterior quantiles |
predict.emc | Generate posterior predictives |
prior | Prior specification |
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_p_vector | Get model parameters from a design |
samples_LNR | An emc object of an LNR model of the Forstmann dataset using the first three subjects |
subset.emc | Shorten an emc object |
summary.emc | Summary statistics for emc objects |