R: Cognitive Models

# Cognitive Models

## Documentation for package ‘ggdmc’ version 0.2.6.2

- DESCRIPTION file
- Package README

## Help Pages

BPIC | Deviance information criteria
BuildDMI | Bind data and models
BuildModel | Create a model object
BuildPrior | Specifying Parameter Prior Distributions
CheckConverged | Model checking functions
check_pvec | Does a model object specify a correct p.vector
ConvertChains | Prepare posterior samples for plotting functions version 1
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
DIC | Deviance information criteria
dlnorm_l | A modified dlnorm functions
dtnorm | Truncated Normal Distribution
effectiveSize | Calculate effective sample sizes
effectiveSize_hyper | Calculate effective sample sizes
effectiveSize_many | Calculate effective sample sizes
effectiveSize_one | Calculate effective sample sizes
gelman | Potential scale reduction factor
GetNsim | Get a n-cell matrix
GetParameterMatrix | Constructs a ns x npar matrix,
GetPNames | Extract parameter names from a model object
get_os | Retrieve information of operating system
ggdmc | Bayeisan computation of response time models
hgelman | Potential scale reduction factor
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
phi2mcmclist | Convert theta to a mcmc List
PickStuck | Which chains get stuck
plot.prior | Plot prior distributions
plot_prior | Plot prior distributions
print.dmi | Create a model object
print.model | Create a model object
print.prior | Print Prior Distribution
ptnorm | Truncated Normal Distribution
random | Generate random numbers
rlba_norm | Generate Random Responses of the LBA Distribution
rprior | Parameter Prior Distributions
rtnorm | Truncated Normal Distribution
run | Start new model fits
simulate.model | Simulate response time data
StartNewsamples | Start new model fits
summary.model | Summarise posterior samples
summary_mcmc_list | Summary statistic for posterior samples
TableParameters | Table response and parameter
theta2mcmclist | Convert theta to a mcmc List
unstick_one | Unstick posterios samples (One subject)