BuildDMI                Bind data and models
BuildModel              Create a model object
BuildPrior              Specifying Parameter Prior Distributions
ConvertChains           Prepare posterior samples for plotting
                        functions version 1
DIC                     Deviance information criteria
GetNsim                 Get a n-cell matrix
GetPNames               Extract parameter names from a model object
GetParameterMatrix      Constructs a ns x npar matrix,
PickStuck               Which chains get stuck
StartNewsamples         Start new model fits
TableParameters         Table response and parameter
check_pvec              Does a model object specify a correct p.vector
dbeta_lu                A modified dbeta function
dcauchy_l               A modified dcauchy functions
dconstant               A pseudo constant function to get constant
                        densities
deviance.model          Calculate the statistics of model complexity
dgamma_l                A modified dgamma function
dlnorm_l                A modified dlnorm functions
dtnorm                  Truncated Normal Distribution
effectiveSize_hyper     Calculate effective sample sizes
gelman                  Potential scale reduction factor
get_os                  Retrieve information of operating system
ggdmc                   Bayeisan computation of response time models
iseffective             Model checking functions
isflat                  Model checking functions
ismixed                 Model checking functions
isstuck                 Model checking functions
likelihood              Calculate likelihoods
mcmc_list.model         Create a MCMC list
plot_prior              Plot prior distributions
print.prior             Print Prior Distribution
random                  Generate random numbers
rlba_norm               Generate Random Responses of the LBA
                        Distribution
rprior                  Parameter Prior Distributions
simulate.model          Simulate response time data
summary.model           Summarise posterior samples
summary_mcmc_list       Summary statistic for posterior samples
theta2mcmclist          Convert theta to a mcmc List
unstick_one             Unstick posterios samples (One subject)
