BayesTreePriorOrthogonalInf {BayesTreePrior} | R Documentation |
Generate n_{iter}
trees from the prior distribution in the unrealistic case where we assume that the number of variables and possible splits are infinite (therefore P(T) is not dependent on the design matrix X) (Case #2).
BayesTreePriorOrthogonalInf(alpha, beta, n_iter = 500)
alpha |
base parameter of the tree prior, |
beta |
power parameter of the tree prior, |
n_iter |
number of trees to generate, |
Returns a list containing, in the following order: the mean number of bottom nodes, the standard deviation of the number of bottom nodes, the mean of the depth, the standard deviation of the depth and a data.frame of vectors (b_i,d_i)
, where b_i
is the number of bottom nodes and d_i
is the depth of the i
th generated tree (i=1, \ldots ,n_{iter}
).
BayesTreePriorOrthogonal
, BayesTreePriorNotOrthogonal
results = BayesTreePriorOrthogonalInf(.95,.5)