plot.tgp: Plotting for Treed Gaussian Process Models
Description
Usage
Arguments
Value
Note
Author(s)
References
See Also
A generic function for plotting of "tgp"
class objects.
1d posterior mean and error plots, 2d posterior mean and
error image and perspective plots, and 3+dimensional mean and error
image and perspective plots are supported via projection
and slicing.
 ## S3 method for class 'tgp'
plot(x, pparts = TRUE, proj = NULL, slice = NULL,
map = NULL, as = NULL, center = "mean", layout = "both",
main = NULL, xlab = NULL, ylab = NULL, zlab = NULL, pc = "pc",
gridlen = c(40,40), span = 0.1,
legendloc = "topright", maineff = TRUE, mrlayout="both",
rankmax = 20, ...)

x 
"tgp" class object that is the output of one of
the b* functions: blm , btlm
bgp , bgpllm , btgp , or
btgpllm

pparts 
If TRUE , partitionregions are plotted (default),
otherwise they are not

proj 
1or2Vector describing the dimensions to be shown in a
projection. The argument is ignored for 1d data, i.e., if x$d
== 1 . For 2d data, no projection needs be specified— the
default argument (proj = NULL ) will result in a 2d perspective
or image plot. 1d projections of 2d or higher data are are
supported, e.g., proj = c(2) would show the second variable
projection. For 3d data or higher, proj=NULL defaults to
proj = c(1,2) which plots a 2d projection for the first two
variables. Slices have priority over the projections—
see next argument (slice )— when nonnull arguments are
provided for both.

slice 
list object with x and z fields, which
are vectors of equal length describing the slice to be plotted, i.e.,
which zvalues of the x$d  2 inputs x$X and
x$XX should be fixed to in order to obtain a 2d visualization.
For example, for 4d data, slice = list(x=(2,4), z=c(0.2, 1.5) will
result in a 2d plot of the first and third dimensions which have
the second and fourth slice fixed at 0.5 and 1.5. The default is
NULL , yielding to the proj argument. Argument is
ignored for 1d data, i.e., if x$d == 1

map 
Optional 2d map (longitude and latitude)
from maps to be shown on top of image plots

center 
Default center = "mean" causes the posterior
predictive mean to be plotted as the centering statistic.
Otherwise the median can be used with center = "med" , or the
kriging mean with center = "km"

as 
Optional string indicator for plotting of adaptive sampling
statistics: specifying as = "alm" for ALM, as = "s2"
for predictive variance, as = "ks2" for expected kriging
variance, as = "alc" for ALC,
and as = "improv" for expected improvement (about the
minimum, see the rankmax argument below).
The default as = NULL plots errorbars (1dplots) or
error magnitudes (2dplots), which is essentially the same as
as = "alm"

layout 
Specify whether to plot the mean predictive surface
(layout = "surf" ), the error or adaptive sampling statistics
(layout = "as" ), or default (layout = "both" ) which
shows both. If layout = "sens" , plot the results of a
sensitivity analysis (see sens ) in a format determined
by the argument maineff below.

main 
Optional character string to add to the main title of the plot

xlab 
Optional character string to add to the x label of the plots

ylab 
Optional character string to add to the y label of the plots

zlab 
Optional character string to add to the z label of the plots;
ignored unless pc = "p"

pc 
Selects perspectiveposterior mean and imageerror plots
(pc = "pc" , the default) or a double–image plot (pc
= "c" )

(only valid for 2d plots)
gridlen 
Number of regular grid points for 2d slices and
projections in x and y. The default of gridlen = c(40,40)
causes a 40 * 40
grid of X , Y , and Z values to be computed.
Ignored for 1d plots and projections

span 
Span for loess kernel.
The tgp package default (span =
0.1 ) is set lower than the loess default.
Smaller spans can lead to warnings from loess
when the data or predictive locations are sparse and ugly plots may
result. In this case, try increasing the span

legendloc 
Location of the legend included in the
plots of sensitivity analyses produced with layout = "sens" ,
or 1d plots of multiresolution models (with corr = "mrexpsep" )
and option mrlayout = "both" ; otherwise the argument is ignored

maineff 
Format for the plots of sensitivity analyses produced
with layout = "sens" ; otherwise the argument is ignored.
If maineff=TRUE main effect plots are produced
alongside boxplots for posterior samples of the sensitivity indices,
and if FALSE only the boxplots are produced. Alternatively,
maineff can be a matrix containing input dimensions in the
configuration that the corresponding main effects are to be plotted;
that is, mfrow=dim(maineff) . In this case, a 90 percent
interval is plotted with each main effect and the sensitivity index
boxplots are not plotted.

mrlayout 
The plot layout for double resolution
tgp objects with params$corr == "mrexpsep" . For the default
mrlayout="both" , the coarse and fine fidelity are plotted
together, either on the same plot for 1D inputs or through
sidebyside image plots of the predicted center with axis
determined by proj for inputs of greater dimension.
Note that many of the standard arguments – such as slice ,
pc , and map – are either nonapplicable or
unsupported for mrlayout="both" . If mrlayout="coarse"
or mrlayout="fine" , prediction for the respective fidelity is
plotted as usual and all of the standard options apply.

rankmax 
When as = "improv" is provided, the posterior
expected improvements are plotted according the the first column
of the improv field of the "tgp" class object.
Text is added to the plot near the XX positions of the first
1:rankmax predictive locations with the highest ranks in the
second column of the improv field.

... 
Extra arguments to 1d (plot ) and 2d plotting
functions persp and image

The only output of this function is beautiful plots
This plotting function is provided with the intention that it
will be used as an aid in the visualization of "tgp"
class
objects. Users are encouraged to use the source code for
this function in order to develop custom plotting functions.
1d projections for 3d or higher data are also available
by specifying a 1d projection argument (e.g. proj=c(1)
for projecting onto the first input variable).
For examples, see vignette("tgp")
and the
help files of those functions in "See Also", below
Robert B. Gramacy, rbgramacy@chicagobooth.edu, and
Matt Taddy, taddy@chicagobooth.edu
http://bobby.gramacy.com/r_packages/tgp
plot
, bgpllm
, btlm
,
blm
, bgp
, btgpllm
,
predict.tgp
,
tgp.trees
, mapT
, loess
, sens