vis.gam {mgcv} | R Documentation

## Visualization of GAM objects

### Description

Produces perspective 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="topo",se=-1,type="link",zlim=NULL,...)

### Arguments

`x` | a `gam` object, produced by `gam()`
`view` | an array containing the names of the two predictor variables to be displayed on the x and y dimensions of the plot. If omitted the first two suitable variables will be used
`cond` | a named list of the values to use for the other predictor variables (not in `view`). Variables omitted from this list will have their values set to their mean for continuous variables, or first level for factors.
`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"` or `"terrain"`.
`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.
`zlim` | a two item array giving the lower and upper limits for the z-axis scale. `NULL` to choose automatically.
`...` | other options to pass on to `persp`. 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 variables supplied 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`

### Value

Simply produces a plot.

### Author(s)

Simon Wood simon@stats.gla.ac.uk

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=0.75),theta=210,phi=40,too.far=0.07)
    # ..... areas where there is no data are not plotted
    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

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