Description Usage Arguments Value Author(s) References Examples
Build Stan models from directed acyclic graph of an object of class bayesvl
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  # build Stan models from directed acyclic graph.
bvl_model2Stan(dag, ppc = "")
# compile and simulate samples from the model.
bvl_modelFit(dag, data, warmup = 1000, iter = 5000, chains = 2, ppc = "", ...)
# summarize the stan priors used for the model.
bvl_stanPriors(dag)
# summarize the stan parameters used for the model.
bvl_stanParams(dag)
# summarize the generated formula at the node.
bvl_formula(dag, nodeName, outcome = T, re = F)

dag 
an object of class 
data 
a data frame or list containing the data 
warmup 
Optional: Number of warmup iterations. By default, half of iter 
iter 
Optional: Number of iterations of sampling. Default is 5000 
chains 
Optional: Number of independent chains to sample from. Default is 2 
ppc 
Optional: a character string contains posterior predictive check scripts 
... 
extra arguments from the generic method 
nodeName 
A character string contains the node name 
outcome 
Optional: Whether show out distribution 
re 
Optional: Whether run recursive for all uplevel nodes 
bvl_model2Stan()
return character string of rstan code generated from the model.
bvl_modelFit()
return an object class bayesvl
which contains result with the following slots.
model 
Stan model code 
stanfit 

standata 
The data 
pars 
Parameter names monitored in samples 
formula 
Generated formula from the model 
bvl_stanPriors()
return character string of rstan priors generated from the model.
bvl_stanParams()
return character string of rstan parameters generated from the model.
La VietPhuong, Vuong QuanHoang
For documentation, case studies and worked examples, and other tutorial information visit the References section on our Github:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  # Design the model in directed acyclic graph
model < bayesvl()
model < bvl_addNode(model, "Lie", "binom")
model < bvl_addNode(model, "B", "binom")
model < bvl_addNode(model, "C", "binom")
model < bvl_addNode(model, "T", "binom")
model < bvl_addArc(model, "B", "Lie", "slope")
model < bvl_addArc(model, "C", "Lie", "slope")
model < bvl_addArc(model, "T", "Lie", "slope")
# Generate the Stan model's code
model_string < bvl_model2Stan(model)
cat(model_string)
# Show priors in generated Stan model
bvl_stanPriors(model)

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