eval.stage {delt} R Documentation

## 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

### Author(s)

Jussi Klemela

`eval.greedy`, `eval.stage.gauss`

### Examples

```dendat<-sim.data(n=200,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)

```

[Package delt version 0.8.0 Index]