# BayesTreePriorOrthogonal: Simulation of the tree prior in the case where we have one... In BayesTreePrior: Bayesian Tree Prior Simulation

## Description

Generate n_{iter} trees from the prior distribution in the case where we have one variable with a finite number of observations (Case #3).

## Usage

 1 BayesTreePriorOrthogonal(alpha, beta, n_obs, n_iter = 500) 

## Arguments

 alpha base parameter of the tree prior, α \in [0,1). beta power parameter of the tree prior, beta ≥q 0. n_obs number of unique observations, n_{obs}>1. 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 ith generated tree (i=1, … ,n_{iter}).

## See Also

BayesTreePriorOrthogonalInf, BayesTreePriorNotOrthogonal

## Examples

 1 2 results1 = BayesTreePriorOrthogonal(.95,.5, 100) results2 = BayesTreePriorOrthogonal(.95,.5, 250) 

BayesTreePrior documentation built on May 29, 2017, 5:40 p.m.