exclude.too.far {mgcv} | R Documentation

## Exclude prediction grid points too far from data

### Description

Takes two arrays defining the nodes of a grid over a 2D covariate space and two arrays defining the location of data in that space, and returns a logical vector with elements `TRUE` if the corresponding node is too far from data and `FALSE` otherwise. Basically a service routine for `vis.gam` and `plot.gam`.

### Usage

    exclude.too.far(g1,g2,d1,d2,dist)

### Arguments

`g1` | co-ordinates of grid relative to first axis.
`g2` | co-ordinates of grid relative to second axis.
`d1` | co-ordinates of data relative to first axis.
`d2` | co-ordinates of data relative to second axis.
`dist` | how far away counts as too far. Grid and data are first scaled so that the grid lies exactly in the unit square, and `dist` is a distance within this unit square.

### Details

Linear scalings of the axes are first determined so that the grid defined by the nodes in `g1` and `g2` lies exactly in the unit square (i.e. on [0,1] by [0,1]). These scalings are applied to `g1`, `g2`, `d1` and `d2`. The minimum Euclidean distance from each node to a datum is then determined and if it is greater than `dist` the corresponding entry in the returned array is set to `TRUE` (otherwise to `FALSE`). The distance calculations are performed in compiled code for speed without storage overheads.

### Value

A logical array with `TRUE` indicating a node in the grid defined by `g1`, `g2` that is `too far' from any datum.

### Author(s)

Simon N. Wood simon@stats.gla.ac.uk

### References

http://www.stats.gla.ac.uk/~simon/

### See Also

`vis.gam`

### Examples

    library(mgcv)
    x<-rnorm(100);y<-rnorm(100) # some "data"
    n<-40 # generate a grid....
    mx<-seq(min(x),max(x),length=n)
    my<-seq(min(y),max(y),length=n)
    gx<-rep(mx,n);gy<-rep(my,rep(n,n))
    tf<-exclude.too.far(gx,gy,x,y,0.1)
    plot(gx[!tf],gy[!tf],pch=".");points(x,y,col=2)

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