Description Usage Arguments Details Value Acknowledgments Note Author(s) References See Also
Function for plotting the crossvalidated survival distributions of a sbh
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 18 19 
object 
Object of class 
main 

xlab 

ylab 

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

col 

lty 

lwd 

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
.
This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University. This project was partially funded by the National Institutes of Health NIH  National Cancer Institute (R01CA160593) to JE. Dazard and J.S. Rao.
Enduser plotting function.
"JeanEudes Dazard, Ph.D." [email protected]
"Michael Choe, M.D." [email protected]
"Michael LeBlanc, Ph.D." [email protected]
"Alberto Santana, MBA." [email protected]
Maintainer: "JeanEudes Dazard, Ph.D." [email protected]
Dazard JE. and Rao J.S. (2017). "Variable Selection Strategies for HighDimensional Survival Bump Hunting using Recursive Peeling Methods." (in prep).
DiazPachon D.A., Dazard JE. and Rao J.S. (2017). "Unsupervised Bump Hunting Using Principal Components." In: Ahmed SE, editor. Big and Complex Data Analysis: Methodologies and Applications. Contributions to Statistics, vol. Edited Refereed Volume. Springer International Publishing, Cham Switzerland, p. 325345.
Yi C. and Huang J. (2016). "Semismooth Newton Coordinate Descent Algorithm for ElasticNet Penalized Huber Loss Regression and Quantile Regression." J. Comp Graph. Statistics, DOI: 10.1080/10618600.2016.1256816.
Dazard JE., Choe M., LeBlanc M. and Rao J.S. (2016). "Crossvalidation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods." Statistical Analysis and Data Mining, 9(1):1242.
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, p. 650664.
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. and J.S. Rao (2010). "Local Sparse Bump Hunting." J. Comp Graph. Statistics, 19(4):90092.
plot.survfit
(R package survival)
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