rrp.dist: RRP dissimilarity matrix
In rrp: Random Recursive Partitioning

Description Usage Arguments Details Value Author(s) References See Also

Main piece of the RRP algorithm which generates the RRP dissimilarity matrix.

1 2	rrp.dist(X, treated = NULL, msplit = 10, Rep = 250, cut.in = 15, check.bal = FALSE, plot = FALSE, asdist = FALSE, verbose = 0)

`X`	a `data.frame` object
`treated`	optional class indicator variable
`msplit`	minimum split parameter in the `rpart` algorithm
`Rep`	number of RRP replications
`cut.in`	number of breaks in which to cut continuous variables
`check.bal`	indicator function. If `TRUE` balance check using hyper-rectangles will be used inside leaves
`plot`	wheter to plot the porximity matrix as image
`asdist`	if `TRUE` returns an object of class `dist`
`verbose`	if greater than 1 some information is printed

This algorithm allows for missing data in X. From version 1.6 of the package the RRP matrix is stored as an external pointer to avoid duplications. This allow to work on bigger datasets.

an object of class externalptr, XPtr or dist

S.M. Iacus

Iacus, S.M., Porro, G. (2009) Random Recursive Partitioning: a matching method for the estimation of the average treatment effect, Journal of Applied Econometrics, 24, 163-185.

Iacus, S.M., Porro, G. (2007) Missing data imputation, matching and other applications of random recursive partitioning, Computational Statistics and Data Analysis, 52, 2, 773-789.

rpart

rrp documentation built on May 2, 2019, 5:25 p.m.