eval.greedy: Returns a greedy histogram
In delt: Estimation of Multivariate Densities Using Adaptive Partitions

Description Usage Arguments Value Author(s) See Also Examples

Returns a greedy histogram. A greedy histogram is grown stagewise by minimizing an empirical risk functional.

1 2	eval.greedy(dendat, leaf, method = "loglik", minobs = NULL, bound = 0, suppo = NULL)

`dendat`	n*d data matrix
`leaf`	the (maximal) number of rectangles in the partition of the histogram
`method`	"loglik" or "projec"; the empirical risk is either the log-likelihood or the L2 empirical risk
`minobs`	non-negative integer; splitting of a bin will be continued if the bin containes "minobs" or more observations
`bound`	internal
`suppo`	2*d vector of real numbers; the rectangle to be splitted; the rectangle has to contain the data

An evaluation tree

Jussi Klemela

lstseq.greedy, partition

library(denpro)
dendat<-sim.data(n=200,seed=5,type="mulmodII")
eva<-eval.greedy(dendat,leaf=15)

dp<-draw.pcf(eva,pnum=c(60,60))         
persp(dp$x,dp$y,dp$z,theta=-20,phi=30)