acf.dmc | Plot an Autocorrelation Matrix |
censor | Censor missing values and RT outliers |
data.model.dmc | Bind Data and Models |
ddmc | Compute Probability Density of Drift-Diffusion Model |
density.dmc | Calculate Probability Density for an Experimental Condition |
dprior | Calculate Prior Probability Density for an EAM |
Dstats.ddm | Calculate Dstats of DDM Density |
dtnorm | Truncated Normal Distribution |
effectiveSize.dmc | Effective Sample Size for Estimating the Mean |
fac2df | Convert factor levels to a data frame |
gelman.diag.dmc | Gelman and Rubin Convergence Diagnostic |
getAccumulatorMatrix | Map a parameter vector to an accumulator matrix |
get_os | get_os Function |
ggdmc | Supersonic DMC |
g_minus | Calculate Drift-diffusion Probability Density |
h.run.dmc | Fit an EAM with Multiple Participants |
h.samples.dmc | Set up a DMC Sample with Multiple Participants |
h.simulate.dmc | Simulate Choice-RT Data for Multiple Participants |
initialise_data | Set up a DMC Sample for a Participant |
initialise_hyper | Set up a DMC Sample for Multiple Participants |
likelihood | Calculate Log-Likelihood |
mcmc.list.dmc | Create a mcmc.list in DMC format |
model.dmc | Creating a Model Object |
pairs.dmc | Create a Plot Matrix of Posterior Simulations |
p.df.dmc | Gets Parameter Data Frame |
phi.as.mcmc.list | Convert Phi to a Theta Vector |
pick.stuck.dmc | Find Stuck Chains |
plot_cell_density | Plot Distributions for Each Cell |
plot_dist | Plot Cell Density |
plot.dmc | Plot DMC Samples |
plot.dmc.list | Plot a DMC Sample with Multiple Participants |
plot.hyper | Plot DMC Samples at the Hyper level |
plot.pp.ggdmc | Posterior Predictive Plot |
plot_prior | Plot Prior Probability Density |
plot_priors | Plot Prior Probability Density |
post.predict.ggdmc | Simulate Post-predictive Sample |
print_cell_p | Print accumulator x internal parameter type matrix for each... |
prior.p.dmc | Makes a list of prior distribution parameters. |
profile.dmc | Profile a DMC Object |
rprior | Generate Random Numbers from Prior Probability Distribution |
run_data | Run a Bayesian EAM Model for Fixed-effect or Random-effect |
run.dmc | run function |
samples.dmc | Initialising a DMC samples |
simulate.dmc | Simulate Responses from an EAM |
summary.dmc | Summarise a DMC Sample with One Participant |
summary.dmc.list | Summarise a DMC Sample with Multiple Participants |
summary.hyper | Summarise a DMC Sample with Multiple Participant at the... |
summed_log_likelihood | Sum and Log Probability Density of a EAM model |
summed_log_prior | Sum and Log Prior Density of a EAM model |
theta.as.mcmc.list | Convert Theta to a mcmc List |
transform | Transform Parameter Data Frame |
view | Inspect Prior Distribution Settings |
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