Man pages for ggdmc
Cognitive Models
| BuildDMI | Bind data and models |
| BuildModel | Create a model object |
| BuildPrior | Specifying Parameter Prior Distributions |
| 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 |
| gelman | Potential scale reduction factor |
| GetNsim | Get a n-cell matrix |
| get_os | Retrieve information of operating system |
| GetParameterMatrix | Constructs a ns x npar matrix, |
| GetPNames | Extract parameter names from a model object |
| 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 log likelihoods |
| mcmc_list.model | Create a MCMC list |
| PickStuck | Which chains get stuck |
| plot_prior | Plot prior distributions |
| print.prior | Print Prior Distribution |
| random | Generate random numbers |
| rlba_norm | Generate Random Deviates of the LBA Distribution |
| rprior | Parameter Prior Distributions |
| simulate.model | Simulate response time data |
| StartNewsamples | Start new model fits |
| summary_mcmc_list | Summary statistic for posterior samples |
| summary.model | Summarise posterior samples |
| TableParameters | Table response and parameter |
| theta2mcmclist | Convert theta to a mcmc List |
| unstick_one | Unstick posterios samples (One subject) |
