prior {bayesplay} | R Documentation |
Specify a prior
Description
Define priors using different different distribution families
Usage
prior(family, ...)
Arguments
family |
the prior distribution (see details) |
... |
see details |
Details
Available distribution families
The following distributions families can be used for the prior
-
normal
a normal distribution -
student_t
a scaled and shifted t-distribution -
cauchy
a Cauchy distribution -
uniform
a uniform distribution -
point
a point -
beta
a beta distribution The parameters that need to be specified will be dependent on the family
Normal distribution
When family
is set to normal
then the following
parameters may be be set
-
mean
mean of the normal prior -
sd
standard deviation of the normal prior -
range
(optional) a vector specifying the parameter range
Student t distribution
When family
is set to student_t
then the following
parameters may be set
-
mean
mean of the scaled and shifted t prior -
sd
standard deviation of the scaled and shifted t prior -
df
degrees of freedom of the scaled and shifted t prior -
range
(optional) a vector specifying the parameter range
Cauchy distribution
When family
is set to cauchy
then the following
parameters may be set
-
location
the centre of the Cauchy distribution (default: 0) -
scale
the scale of the Cauchy distribution -
range
(optional) a vector specifying the parameter range
Uniform distribution
When family
is set to uniform
then the following
parameters must be set
-
min
the lower bound -
max
the upper bound
Point
When family
is set to point
then the following
parameters may be set
-
point
the location of the point prior (default: 0)
Beta
When family
is set to beta
then the following
parameters may be set
-
alpha
the first shape parameter -
beta
the second shape parameter
Value
an object of class prior
Examples
# specify a normal prior
prior(family = "normal", mean = 0, sd = 13.3)
# specify a half-normal (range 0 to Infinity) prior
prior(family = "normal", mean = 0, sd = 13.3, range = c(0, Inf))
# specify a student t prior
prior(family = "student_t", mean = 0, sd = 13.3, df = 79)
# specify a truncated t prior
prior(family = "student_t", mean = 0, sd = 13.3, df = 79, range = c(-40, 40))
# specify a cauchy prior
prior(family = "cauchy", location = 0, scale = .707)
# specify a half cauchy prior
prior(family = "cauchy", location = 0, scale = 1, range = c(-Inf, 0))
# specify a uniform prior
prior(family = "uniform", min = 0, max = 20)
# specify a point prior
prior(family = "point", point = 0)
# specify a beta prior
prior(family = "beta", alpha = 2.5, beta = 3.8)