delt (version 0.8.2)

eval.stage: Returns a stagewise minimization estimate

Description

Returns a stagewise minimization estimate. A stagewise minimization estimator is a convex combination of greedy histograms. The convex combination is constructed by a stagewise minimization of an empirical risk functional.

Usage

eval.stage(dendat, leaf, M, pis = NULL, mcn = dim(dendat)[1], 
minobs = NULL, seedi = 1, method = "projec", bound = 0)

Arguments

dendat

n*d data matrix

leaf

the (maximal) number of rectangles in the partition of the greedy histograms

M

the number of histograms in the convex combination

pis

the vector of weights of the convex combination

mcn

the size of the Monte Carlo sample used in the numerical integration in calculating the empirical risk functional

minobs

non-negative integer; splitting of a bin of a greedy histogram will be continued if the bin containes "minobs" or more observations

seedi

the seed for the generation of the Monte Carlo sample

method

"loglik" or "projec"; the empirical risk is either the log-likelihood or the L2 empirical risk

bound

internal

Value

An evaluation tree

See Also

eval.greedy, eval.stage.gauss

Examples

library(denpro)
dendat<-sim.data(n=100,seed=5,type="mulmodII")
leaf<-13  # the number of leafs of the greedy histograms
M<-5      # the number of greedy histograms

pcf<-eval.stage(dendat,leaf=leaf,M=M)

dp<-draw.pcf(pcf,pnum=c(120,120))
persp(dp$x,dp$y,dp$z,ticktype="detailed",phi=25,theta=-120)