Description Usage Arguments Value See Also Examples
Generate n_{iter} trees from the prior distribution in the case where we have one variable with a finite number of observations (Case #3).
1 | BayesTreePriorOrthogonal(alpha, beta, n_obs, n_iter = 500)
|
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. |
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}).
BayesTreePriorOrthogonalInf
, BayesTreePriorNotOrthogonal
1 2 | results1 = BayesTreePriorOrthogonal(.95,.5, 100)
results2 = BayesTreePriorOrthogonal(.95,.5, 250)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.