bartModelMatrix: Create a matrix out of a vector or data.frame

In BART: Bayesian Additive Regression Trees

Create a matrix out of a vector or data.frame

Description

The external BART functions operate on matrices in memory. Therefore, if the user submits a vector or data.frame, then this function converts it to a matrix. Also, it determines the number of cutpoints necessary for each column when asked to do so.

Usage

bartModelMatrix(X, numcut=0L, usequants=FALSE, type=7,
                rm.const=FALSE, cont=FALSE, xinfo=NULL)

Arguments

X	A vector or data.frame to create the matrix from.
numcut	The maximum number of cutpoints to consider. If numcut=0, then just return a matrix; otherwise, return a list containing a matrix X, a vector numcut and a list xinfo.
usequants	If usequants is FALSE, then the cutpoints in xinfo are generated uniformly; otherwise, if TRUE, then quantiles are used for the cutpoints.
type	Determines which quantile algorithm is employed.
rm.const	Whether or not to remove constant variables.
cont	Whether or not to assume all variables are continuous.
xinfo	You can provide the cutpoints to BART or let BART choose them for you. To provide them, use the xinfo argument to specify a list (matrix) where the items (rows) are the covariates and the contents of the items (columns) are the cutpoints.

See Also

class.ind

Examples

set.seed(99)

a <- rbinom(10, 4, 0.4)

table(a)

x <- runif(10)

df <- data.frame(a=factor(a), x=x)

b <- bartModelMatrix(df)

b

b <- bartModelMatrix(df, numcut=9)

b

b <- bartModelMatrix(df, numcut=9, usequants=TRUE)

b

## Not run: 
    f <- bartModelMatrix(as.character(a))

## End(Not run)

BART documentation built on June 22, 2024, 11:33 a.m.