Function for plotting the crossvalidated survival distributions of a PRSP
object.
Plot the crossvalidated KaplanMeir estimates of survival distributions for the highest risk (inbox) versus
lowerrisk (outbox) groups of samples at each iteration of the peeling sequence (inner loop of our PRSP algorithm).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 
object 
Object of class 
main 

xlab 

ylab 

precision 
Precision of crossvalidated logrank pvalues of separation between two survival curves. Defaults to 1e3. 
mark 

col 

cex 

steps 

nr 

nc 

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 "Survival Plots". 
path 
Absolute path (without final (back)slash separator). Defaults to the working directory path. 
horizontal 

width 

height 

... 
Generic arguments passed to other plotting functions, including 
Some of the plotting parameters are further defined in the function plot.survfit
(R package survival).
Step #0 always corresponds to the situation where the starting box covers the entire testset data before peeling.
Crossvalidated LRT, LHR of inbox samples and logrank pvalues of separation are shown at the bottom of the plot
with the corresponding peeling step. Pvalues are lowerbounded by the precision limit given by 1/A,
where A is the number of permutations.
Invisible. None. Displays the plot(s) on the specified device
.
Enduser plotting function.
"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.
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.
plot.survfit
(R package survival)
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  #===================================================
# 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_boxkm(object = CVCOMB.synt1,
main = paste("Crossvalidated probability curves for model #1", sep=""),
xlab = "Time", ylab = "Probability",
device = NULL, file = "Survival Plots", path=getwd(),
horizontal = TRUE, width = 11, height = 8.5)

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