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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,...)
Simply produces a plot.
a gam
object, produced by gam()
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.
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.
The number of grid nodes in each direction used for calculating the plotted surface.
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.
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.
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.
sets the colour of contours when using plot.type="contour"
. Default scheme used if NULL
.
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.
"link"
to plot on linear predictor scale and "response"
to plot on the response scale.
one of "contour"
or "persp"
.
a two item array giving the lower and upper limits for the z-axis
scale. NULL
to choose automatically.
The number of colors to use in color schemes.
selects the linear predictor for models with more than one.
other options to pass on to persp
,
image
or contour
. In particular ticktype="detailed"
will add proper axes
labelling to the plots.
Simon Wood simon.wood@r-project.org
Based on an original idea and design by Mike Lonergan.
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.
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
.
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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