mgcv (version 0.9-6)

vis.gam: 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. Replaces persp.gam.

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

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 th

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 value

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.

Value

• Simply produces a plot.

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

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