R: Kernel smoothing on a 1D, 2D or 3D grid

kernsm {aws} | R Documentation

## Kernel smoothing on a 1D, 2D or 3D grid

### Description

Performs Kernel smoothing on a 1D, 2D or 3D grid by fft

### Usage

    kernsm(y, h = 1, kern = "Gaussian", m = 0, nsector = 1, sector = 1,
           symmetric = FALSE, unit = c("SD","FWHM"))

### Arguments

`y` | Object of class `"array"` containing the original (response) data on a grid
`h` | bandwidth
`kern` | Determines the kernel function. Object of class `"character"` kernel, can be any of `c("Gaussian","Uniform","Triangle","Epanechnicov","Biweight","Triweight")`. Defaults to `kern="Gaussian"`
`m` | Object of class `"integer"` vector of length `length(dy)` determining the order of derivatives specified for the coordinate directios.
`nsector` | number of sectors to use. Positive weights are restricted to the sector selected by `sector`
`sector` | Object of class `"integer"` between `1` and `nsector`. sector used.
`symmetric` | Object of class `"logical"` determines if sectors are symmetric with respect to the origin.
`unit` | How should the bandwidth be interpreted in case of a Gaussian kernel. For `"SD"` the bandwidth refers to the standard deviation of the kernel while `"FWHM"` interprets the banwidth in terms of Full Width Half Maximum of the kernel.

### Details

In case of `any(m>0)` derivative kernels are generated and applied for the corresponding coordinate directions. If `nsector>1` the support of the kernel is restricted to a circular sector determined by `sector`.

### Value

An object of class `kernsm`

### Author(s)

Joerg Polzehl polzehl@wias-berlin.de

### References

Local Approximation Techniques in Signal And Image Processing, SPIE Society of Photo-Optical Instrumentation Engin., 2006, PM157

### See Also

`kernsm-class`, `ICIsmooth`,`ICIcombined`

[Package aws version 2.4-0 Index]