lstseq.kern {denpro} R Documentation

## Calculates a scale of kernel estimates

### Description

Calculates a scale of kernel estimates corresponding to a scale of smoothing parmeters.

### Usage

```lstseq.kern(dendat, hseq, N, lstree = NULL, level = NULL,
Q = NULL, kernel = "gauss", hw = NULL, algo = "leafsfirst", support = NULL)
```

### Arguments

 `dendat` n*d matrix of real numbers; the data matrix `hseq` a vector of positive real numbers; the sequence should be monotonic `N` vector of d positive integers; the dimension of the grid where the kernel estimate will be evaluated; we evaluate the estimate on a regular grid which contains the support of the kernel estimate `lstree ` if NULL, then level set trees are not calculated `level` NULL or a real number between 0 and 1; if NULL, then shape trees are not calculated; if number, then it is the level in percents of the maximum of the level sets for which the shape trees are calculated `Q` positive integer; needed only in the DynaDecompose algorithm, see parameter "algo"; the number of levels in the level set trees `kernel` "epane" or "gauss"; the kernel is either the Bartlett-Epanechnikov product kernel or the standard Gaussian `hw` positive integer; parameter for time localized kernel estimation; gives the smoothing parameter for the temporal smoothing `algo` "leafsfirst" or "dynadecompose" `support` 2*d vector of reals gives the d intervals of a rectangular support; c(low1,upp1,...,lowd,uppd)

### Value

A list with components

 `lstseq` a list of level set trees `pcfseq` a list of piecewise constant functions `stseq` a list of shape trees `hseq` a vector of smoothing parameters corresponding to the members in the sequences

### Author(s)

Jussi Klemela

`scaletable`

### Examples

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

h1<-0.9
h2<-2.2
lkm<-5
hseq<-hgrid(h1,h2,lkm)

N<-c(16,16)
estiseq<-lstseq.kern(dendat,hseq,N)

```

[Package denpro version 0.9.0 Index]