BayesTreePriorOrthogonalInf: Simulation of the tree prior 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).
Description
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).
base parameter of the tree prior, $\alpha \in [0,1)$.
beta
power parameter of the tree prior, $beta \geq 0$.
n_iter
number of trees to generate, $n_{iter}>0$.
Value
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 ($i=1, \ldots ,n_{iter}$).