run_hurdle  R Documentation 
This function fits a JAGS using the jags
funciton and obtain posterior inferences.
run_hurdle(type, dist_e, dist_c, inits, se, sc, sde, sdc, ppc)
type 
Type of structural value mechanism assumed. Choices are Structural Completely At Random (SCAR), and Structural At Random (SAR). 
dist_e 
distribution assumed for the effects. Current available chocies are: Normal ('norm'), Beta ('beta'), Gamma ('gamma'), Exponential ('exp'), Weibull ('weibull'), Logistic ('logis'), Poisson ('pois'), Negative Binomial ('nbinom') or Bernoulli ('bern') 
dist_c 
distribution assumed for the costs. Current available chocies are: Normal ('norm'), Gamma ('gamma') or LogNormal ('lnorm'). 
inits 
a list with elements equal to the number of chains selected; each element of the list is itself a list of starting values for the BUGS model, or a function creating (possibly random) initial values. If inits is NULL, JAGS will generate initial values for parameters 
se 
Structural value to be found in the effect data. If set to 
sc 
Structural value to be found in the cost data. If set to 
sde 
hyperprior value for the standard deviation of the distribution of the structural effects. The default value is

sdc 
hyperprior value for the standard deviation of the distribution of the structural costs. The default value is

ppc 
Logical. If 
#Internal function only
#No examples
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