densplit: Calculation of an overfitting histogram

In delt: Estimation of Multivariate Densities Using Adaptive Partitions

Description

The function returns an overfitting histogram when a data matrix is given as an input. The output is an evaluation tree which is grown with greedy growing. The evaluation tree defines a partition of the sample space. The evaluation tree may be pruned to get a density estimate.

Usage

densplit(dendat, minobs=NULL, leaf=0, method="loglik", 
splitscan=0, seedf=1, suppo=NULL)

Arguments

dendat	n*d data matrix
minobs	non-negative integer; splitting of a bin will be continued if the bin containes "minobs" or more observations
leaf	internal (maximal number of leafs in the evaluation tree)
method	"loglik" or "projec"; the contrast function
splitscan	internal (random selection of splits)
seedf	internal
suppo	2*d vector of real numbers; the rectangle to be splitted; the rectangle has to contain the data

Value

Returns an evaluation tree as a list of vectors.

direc	integer in 1,...,d; variable which is splitted
split	real number; splitting point
mean	nonnegative number; value of the histogram on the rectangle corresponding to the node
nelem	nonnegative integer; number of observations in the rectangle corresponding to the node
ssr	real number; value of the likelihood criterion
volume	non-negative number; volume of the rectangle corresponding to the node
left	non-negative integer; link to the left child, 0 if terminal node
right	non-negative integer; link to the right child, 0 if terminal node
low	the lower vertice of the rectangles
upp	the upper vertice of the rectangles
N	the number of grid points at each direction
support	the support of the histogram

Author(s)

Jussi Klemela

See Also

prune, eval.pick

Examples

library(denpro)

dendat<-sim.data(n=200,seed=5,type="mulmodII")
et<-densplit(dendat)

treeseq<-prune(et)
treeseq$leafs
len<-length(treeseq$leafs)

leaf<-treeseq$leafs[len-10]
leaf
etsub<-eval.pick(treeseq,leaf=leaf)

dp<-draw.pcf(etsub)
persp(dp$x,dp$y,dp$z,phi=25,theta=-120)

delt documentation built on May 2, 2019, 3:42 p.m.