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BayesTools (version 0.2.18)

prior_spike_and_slab: Creates a spike and slab prior distribution

Description

prior_spike_and_slab creates a spike and slab prior distribution corresponding to the specification in kuo1998variable;textualBayesTools (see ohara2009review;textualBayesTools for further details). I.e., a prior distribution is multiplied by an independent indicator with values either zero or one.

Usage

prior_spike_and_slab(
  prior_parameter,
  prior_inclusion = prior(distribution = "spike", parameters = list(location = 0.5)),
  prior_weights = 1
)

Value

return an object of class 'prior'.

Arguments

prior_parameter

a prior distribution for the parameter

prior_inclusion

a prior distribution for the inclusion probability. The inclusion probability must be bounded within 0 and 1 range. Defaults to prior("spike", parameters = list(location = 0.5)) which corresponds to 1/2 prior probability of including the slab prior distribution (but other prior distributions, like beta etc can be also specified).

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.

See Also

prior()

Examples

Run this code
# create a spike and slab prior distribution
p1 <- prior_spike_and_slab(
   prior(distribution = "normal", parameters = list(mean = 0, sd = 1)),
   prior_inclusion = prior(distribution = "beta", parameters = list(alpha = 1, beta = 1))
)

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