vis.gam  R Documentation 
Produces perspective or contour plot views of gam
model
predictions, fixing all but the values in view
to the values supplied in cond
.
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,lp=1,...)
x 
a 
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 
cond 
a named list of the values to use for the other predictor terms
(not in 
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 
col 
The colours for the facets of the plot. If this is 
color 
the colour scheme to use for plots when 
contour.col 
sets the colour of contours when using 
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 
type 

plot.type 
one of 
zlim 
a two item array giving the lower and upper limits for the zaxis
scale. 
nCol 
The number of colors to use in color schemes. 
lp 
selects the linear predictor for models with more than one. 
... 
other options to pass on to 
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 seethrough) meshes are produced at
mean and +/ se
standard errors. Parts of the xy 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 override the
default values used by vis.gam
.
Simply produces a plot.
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.
Simon Wood simon.wood@rproject.org
Based on an original idea and design by Mike Lonergan.
persp
and gam
.
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= 135) # plot against by variable
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