prior {BayesTools}  R Documentation 
prior
creates a prior distribution.
The prior can be visualized by the plot
function.
prior(
distribution,
parameters,
truncation = list(lower = Inf, upper = Inf),
prior_weights = 1
)
prior_none(prior_weights = 1)
distribution 
name of the prior distribution. The possible options are

parameters 
list of appropriate parameters for a given

truncation 
list with two elements, 
prior_weights 
prior odds associated with a given distribution. The value is passed into the model fitting function, which creates models corresponding to all combinations of prior distributions for each of the model parameters and sets the model priors odds to the product of its prior distributions. 
prior
and prior_none
return an object of class 'prior'.
A named list containing the distribution name, parameters, and prior weights.
plot.prior()
, Normal, Lognormal, Cauchy,
Beta, Exponential,
LocationScaleT, InvGamma.
# create a standard normal prior distribution
p1 < prior(distribution = "normal", parameters = list(mean = 1, sd = 1))
# create a halfnormal standard normal prior distribution
p2 < prior(distribution = "normal", parameters = list(mean = 1, sd = 1),
truncation = list(lower = 0, upper = Inf))
# the prior distribution can be visualized using the plot function
# (see ?plot.prior for all options)
plot(p1)