vis.gam {mgcv} | R Documentation

## Visualization of GAM objects

### Description

Produces perspective or contour plot views of `gam` model predictions, fixing all but the values in `view` to the values supplied in `cond`.

### Usage

    vis.gam(x,view=NULL,cond=list(),n.grid=30,too.far=0,col=NA,
            color="heat",contour.col=NULL,se=-1,type="link",
            plot.type="persp",zlim=NULL,nCol=50,...)

### Arguments

`x` | a `gam` object, produced by `gam()`
`view` | an array containing the names of the two main effect terms to be displayed on the x and y dimensions of the plot. If omitted the first two suitable terms will be used. Note that variables coerced to factors in the model formula won't work as view variables, and `vis.gam` can not detect that this has happened when setting defaults.
`cond` | a named list of the values to use for the other predictor terms (not in `view`). Variables omitted from this list will have the closest observed value to the median for continuous variables, or the most commonly occuring level for factors. Parametric matrix variables have all the entries in each column set to the observed column entry closest to the column median.
`n.grid` | The number of grid nodes in each direction used for calculating the plotted surface.
`too.far` | plot grid nodes that are too far from the points defined by the variables given in `view` can be excluded from the plot. `too.far` determines what is too far. The grid is scaled into the unit square along with the `view` variables and then grid nodes more than `too.far` from the predictor variables are excluded.
`col` | The colours for the facets of the plot. If this is `NA` then if `se`>0 the facets are transparent, otherwise the colour scheme specified in `color` is used. If `col` is not `NA` then it is used as the facet colour.
`color` | the colour scheme to use for plots when `se`<=0. One of `"topo"`, `"heat"`, `"cm"`, `"terrain"`, `"gray"` or `"bw"`. Schemes `"gray"` and `"bw"` also modify the colors used when `se`>0.
`contour.col` | sets the colour of contours when using `plot.type="contour"`. Default scheme used if `NULL`.
`se` | if less than or equal to zero then only the predicted surface is plotted, but if greater than zero, then 3 surfaces are plotted, one at the predicted values minus `se` standard errors, one at the predicted values and one at the predicted values plus `se` standard errors.
`type` | `"link"` to plot on linear predictor scale and `"response"` to plot on the response scale.
`plot.type` | one of `"contour"` or `"persp"`.
`zlim` | a two item array giving the lower and upper limits for the z-axis scale. `NULL` to choose automatically.
`nCol` | The number of colors to use in color schemes.
`...` | other options to pass on to `persp`, `image` or `contour`. In particular `ticktype="detailed"` will add proper axes labelling to the plots.

### Details

The x and y limits are determined by the ranges of the terms named in `view`. If `se`<=0 then a single (height colour coded, by default) surface is produced, otherwise three (by default see-through) meshes are produced at mean and +/- `se` standard errors. Parts of the x-y plane too far from data can be excluded by setting `too.far`

All options to the underlying graphics functions can be reset by passing them as extra arguments `...`: such supplied values will always over-ride the default values used by `vis.gam`.

### Value

Simply produces a plot.

### WARNINGS

The routine can not detect that a variable has been coerced to factor within a model formula, and will therefore fail if such a variable is used as a `view` variable. When setting default `view` variables it can not detect this situation either, which can cause failures if the coerced variables are the first, otherwise suitable, variables encountered.

### Author(s)

Simon Wood simon.wood@r-project.org

Based on an original idea and design by Mike Lonergan.

### See Also

`persp` and `gam`.

### Examples

    library(mgcv)
    set.seed(0)
    n<-200;sig2<-4
    x0 <- runif(n, 0, 1);x1 <- runif(n, 0, 1)
    x2 <- runif(n, 0, 1)
    y<-x0^2+x1*x2 +runif(n,-0.3,0.3)
    g<-gam(y~s(x0,x1,x2))
    old.par<-par(mfrow=c(2,2))
    # display the prediction surface in x0, x1 ....
    vis.gam(g,ticktype="detailed",color="heat",theta=-35)
    vis.gam(g,se=2,theta=-35) # with twice standard error surfaces
    vis.gam(g, view=c("x1","x2"),cond=list(x0=0.75)) # different view
    vis.gam(g, view=c("x1","x2"),cond=list(x0=.75),theta=210,phi=40,
            too.far=.07)
    # ..... areas where there is no data are not plotted

    # contour examples....
    vis.gam(g, view=c("x1","x2"),plot.type="contour",color="heat")
    vis.gam(g, view=c("x1","x2"),plot.type="contour",color="terrain")
    vis.gam(g, view=c("x1","x2"),plot.type="contour",color="topo")
    vis.gam(g, view=c("x1","x2"),plot.type="contour",color="cm")

    par(old.par)

    # Examples with factor and "by" variables

    fac<-rep(1:4,20)
    x<-runif(80)
    y<-fac+2*x^2+rnorm(80)*0.1
    fac<-factor(fac)
    b<-gam(y~fac+s(x))

    vis.gam(b,theta=-35,color="heat") # factor example

    z<-rnorm(80)*0.4
    y<-as.numeric(fac)+3*x^2*z+rnorm(80)*0.1
    b<-gam(y~fac+s(x,by=z))

    vis.gam(b,theta=-35,color="heat",cond=list(z=1)) # by variable example

    vis.gam(b,view=c("z","x"),theta= 35) # plot against by variable

[Package mgcv version 1.7-18 Index]