2D Visualization of Data Scatter and Box Vertices
Description
S3generic plotting function for twodimensional visualization of original data as well as
predicted data scatter with crossvalidated box vertices of a PRSP
object.
The scatter plot is for a given peeling step of the peeling sequence and in a given plane of
the used covariates of the PRSP
object, both specified by the user.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  ## S3 method for class 'PRSP'
plot(x,
main = NULL,
proj = c(1,2),
splom = TRUE,
boxes = FALSE,
steps = x$cvfit$cv.nsteps,
pch = 16,
cex = 0.5,
col = 2:(length(steps)+1),
col.box = 2:(length(steps)+1),
lty.box = rep(2,length(steps)),
lwd.box = rep(1,length(steps)),
add.legend = TRUE,
device = NULL,
file = "Scatter Plot",
path=getwd(),
horizontal = FALSE,
width = 5,
height = 5, ...)

Arguments
x 
Object of class 
main 

proj 

splom 

boxes 

steps 

pch 

cex 

col 

col.box 

lty.box 

lwd.box 

add.legend 

device 
Graphic display device in {NULL, "PS", "PDF"}. Defaults to NULL (standard output screen). Currently implemented graphic display devices are "PS" (Postscript) or "PDF" (Portable Document Format). 
file 
File name for output graphic. Defaults to "Scatter Plot". 
path 
Absolute path (without final (back)slash separator). Defaults to working directory path. 
horizontal 

width 

height 

... 
Generic arguments passed to other plotting functions. 
Details
The scatterplot is drawn on a graphical device with geometrically equal scales on the X and Y axes.
Value
Invisible. None. Displays the plot(s) on the specified device
.
Note
Enduser plotting function.
Author(s)
"JeanEudes Dazard, Ph.D." jxd101@case.edu
"Michael Choe, M.D." mjc206@case.edu
"Michael LeBlanc, Ph.D." mleblanc@fhcrc.org
"Alberto Santana, MBA." ahs4@case.edu
Maintainer: "JeanEudes Dazard, Ph.D." jxd101@case.edu
Acknowledgments: This project was partially funded by the National Institutes of Health NIH  National Cancer Institute (R01CA160593) to JE. Dazard and J.S. Rao.
References
Dazard JE., Choe M., LeBlanc M. and Rao J.S. (2015). "Crossvalidation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods." Statistical Analysis and Data Mining (in press).
Dazard JE., Choe M., LeBlanc M. and Rao J.S. (2014). "CrossValidation of Survival Bump Hunting by Recursive Peeling Methods." In JSM Proceedings, Survival Methods for Risk Estimation/Prediction Section. Boston, MA, USA. American Statistical Association IMS  JSM, p. 33663380.
Dazard JE., Choe M., LeBlanc M. and Rao J.S. (2015). "R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification." In JSM Proceedings, Statistical Programmers and Analysts Section. Seattle, WA, USA. American Statistical Association IMS  JSM, (in press).
Dazard JE. and J.S. Rao (2010). "Local Sparse Bump Hunting." J. Comp Graph. Statistics, 19(4):90092.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30  #===================================================
# Loading the library and its dependencies
#===================================================
library("PRIMsrc")
#=================================================================================
# Simulated dataset #1 (n=250, p=3)
# Non Replicated Combined CrossValidation (RCCV)
# Peeling criterion = LRT
# Optimization criterion = LRT
#=================================================================================
CVCOMB.synt1 < sbh(dataset = Synthetic.1,
cvtype = "combined", cvcriterion = "lrt",
B = 1, K = 5,
vs = TRUE, cpv = FALSE,
decimals = 2, probval = 0.5,
arg = "beta=0.05,
alpha=0.1,
minn=10,
L=NULL,
peelcriterion=\"lr\"",
parallel = FALSE, conf = NULL, seed = 123)
plot(x = CVCOMB.synt1,
main = paste("Scatter plot for model #1", sep=""),
proj = c(1,2), splom = TRUE, boxes = TRUE,
steps = CVCOMB.synt1$cvfit$cv.nsteps,
pch = 16, cex = 0.5, col = 2,
col.box = 2, lty.box = 2, lwd.box = 1,
add.legend = TRUE, device = NULL)
