part.dep {gbev}R Documentation

Partial dependence

Description

Partial dependence function for boosted tree model.

Usage

part.dep(object,varIndx,ngrid=50,
firstTree=NULL,lastTree=NULL,plt=TRUE)

Arguments

object A fitted object of type gbev.object.
varIndx Index of variables to compute partial dependence, can be of length 1 or 2, corresponding univariate and bivariate partial dependence functions.
ngrid Number of grid points along each axis at which to compute partial dependence function.
firstTree Index of tree in boosted tree sequence to start computations, defaults to 1.
lastTree Index of last tree in boosted tree sequence to use for computations, defaults to number of boosting iterations.
plt If TRUE then the partial dependence is plotted.

Details

Computes partial dependence functions used to summarized the marginal effect of covariates on the response. These were introduced in Friedman (2001) and are also described in Hastie et.al. (2001) in chapter 10.13.2. The part.dep function, however, computes the partial dependence of the latent covariates, the X's, on the response, and not the error-contaminated W's. This requires a slight modification of the procedure described in the references. Specifically, Friedman (2001) describes a procedure where to compute the partial dependence using boosted tree models one needs to know the proportion of the observations falling in the various terminal nodes of the trees. With measurement error, however, this proportion is not observable and must be estimated, which here is done using the Monte Carlo samples used in the tree fitting of each boosting iteration.

Value

A list with elements pred, x and dat. If univariate partial dependence, pred is the partial dependence at the points x. If bivariate partial dependence, then dat is a data-frame with the partial dependence given in variable z evaluated at the variables x and y.

References

J.H. Friedman (2001). "Greedy Function Approximation: A Gradient Boosting Machine," Annals of Statistics 29(5):1189-1232.

T. Hastie, R. Tibshirani and J.H. Friedman (2001). "The Elements of Statistical Learning" Springer.


[Package gbev version 0.1.1 Index]