prior_spike_and_slab {BayesTools}  R Documentation 
prior_spike_and_slab
creates a spike and slab prior
distribution corresponding to the specification in
Kuo and Mallick (1998) (see
O'Hara and Sillanpää (2009) for further details). I.e.,
a prior distribution is multiplied by an independent indicator with values
either zero or one.
prior_spike_and_slab(
prior_parameter,
prior_inclusion = prior(distribution = "spike", parameters = list(location = 0.5)),
prior_weights = 1
)
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_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. 
return an object of class 'prior'.
# 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))
)