prior_PEESE | R Documentation |
prior
creates a prior distribution for fitting a PET or
PEESE style models in RoBMA. The prior distribution can be visualized
by the plot
function.
prior_PEESE(
distribution,
parameters,
truncation = list(lower = 0, upper = Inf),
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_PET
and prior_PEESE
return an object of class 'prior'.
plot.prior()
, prior()
# create a half-Cauchy prior distribution
# (PET and PEESE specific functions automatically set lower truncation at 0)
p1 <- prior_PET(distribution = "Cauchy", parameters = list(location = 0, scale = 1))
plot(p1)
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