R: Ratio of two kernel smoothings

kernrat {splancs} | R Documentation

## Ratio of two kernel smoothings

### Description

Return the ratio of two kernel smoothings

### Usage

    kernrat(pts1,pts2,poly,h1,h2,nx=20,ny=20,kernel='quartic')

### Arguments

`pts1,pts2` | Point data sets
`poly` | A polygon data set
`h1,h2` | The kernel width parameters, `h1` for `pts1`, and `h2` for `pts2`
`nx` | Number of points along the x-axis of the returned grid.
`ny` | Number of points along the y-axis of the returned grid.
`kernel` | Type of kernel function to use. Currently only the quartic kernel is implemented.

### Value

A list with the following components:

`x` | List of x-coordinates at which the kernel function has been evaluated.
`y` | List of y-coordinates at which the kernel function has been evaluated.
`z` | A matrix of dimension `nx` by `ny` containing the ratio of the kernel functions.
`h` | A vector of length 2 containing `h1` and `h2`
`kernel` | a character string containing the kernel name.

### References

Berman M. and Diggle P.J. (1989) Estimating Weighted Integrals of the Second-Order Intensity of Spatial Point Patterns. J. R. Statist Soc B51 81-92; Rowlingson, B. and Diggle, P. 1993 Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, 19, 627-655; the original sources can be accessed at: http://www.maths.lancs.ac.uk/~rowlings/Splancs/. See also Bivand, R. and Gebhardt, A. 2000 Implementing functions for spatial statistical analysis using the R language. Journal of Geographical Systems, 2, 307-317.

### See Also

`kernel2d`, `mse2d`

### Examples

    data(okwhite)
    data(okblack)
    okpoly <- list(x=c(okwhite$x, okblack$x), y=c(okwhite$y, okblack$y))
    kr <- kernrat(as.points(okwhite), as.points(okblack), bboxx(bbox(as.points(okpoly))),
     h1=50, h2=50)
    image(kr, asp=1)
    brks <- quantile(c(kr$z), seq(0,1,1/10), na.rm=TRUE)
    lbrks <- formatC(brks, 3, 6, "g", " ")
    cols <- heat.colors(length(brks)-1)
    def.par <- par(no.readonly = TRUE)
    layout(matrix(c(1,0,1,2), 2, 2, byrow = TRUE), c(2.5,1.5), c(1,3), TRUE)
    image(kr, breaks=brks, col=cols, asp=1)
    plot.new()
    legend(c(0,1), c(0,1), legend=paste(lbrks[-length(lbrks)], lbrks[-1], sep=":"), fill=cols, bty="n")
    par(def.par)

[Package splancs version 2.01-40 Index]