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BayesTreePrior (version 1.0.1)

BayesTreePriorOrthogonal: Simulation of the tree prior in the case where we have one single variable (Case #3).

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

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

Arguments

alpha
base parameter of the tree prior, $\alpha \in [0,1)$.
beta
power parameter of the tree prior, $beta \geq 0$.
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 $i$th generated tree ($i=1, \ldots ,n_{iter}$).

See Also

BayesTreePriorOrthogonalInf, BayesTreePriorNotOrthogonal

Examples

Run this code
results1 = BayesTreePriorOrthogonal(.95,.5, 100)
results2 = BayesTreePriorOrthogonal(.95,.5, 250)

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