R: Fits a Trend Surface by Least-squares

surf.ls {spatial} | R Documentation

## Fits a Trend Surface by Least-squares

### Description

Fits a trend surface by least-squares.

### Usage

    surf.ls(np, x, y, z)

### Arguments

`np` | degree of polynomial surface
`x` | x coordinates or a data frame with columns `x`, `y`, `z`
`y` | y coordinates
`z` | z coordinates. Will supersede `x$z`

### Value

list with components

`beta` | the coefficients
`x` |
`y` |
`z` | and others for internal use only.

### References

Ripley, B. D. (1981) Spatial Statistics. Wiley.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

### See Also

`trmat`, `surf.gls`

### Examples

    library(MASS)  # for eqscplot
    data(topo, package="MASS")
    topo.kr <- surf.ls(2, topo)
    trsurf <- trmat(topo.kr, 0, 6.5, 0, 6.5, 50)
    eqscplot(trsurf, type = "n")
    contour(trsurf, add = TRUE)
    points(topo)

    eqscplot(trsurf, type = "n")
    contour(trsurf, add = TRUE)
    plot(topo.kr, add = TRUE)
    title(xlab= "Circle radius proportional to Cook's influence statistic")

[Package spatial version 7.3-12 Index]