Description Usage Arguments Details Value Acknowledgments Note Author(s) References
S3method plot function for twodimensional visualization of scatter of data points
and crossvalidated encapsulating box of a sbh
object for the highest risk (inbox) versus
lowerrisk (outbox) groups (PRSP), and between the two specified fixed groups (PRGSP),
if this option is used. The scatter plot is done for a given peeling step (or number of steps)
of the peeling sequence (inner loop of our PRSP or PRGSP) and in a given plane of the used covariates
of the sbh
object, both specified by the user.
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  ## S3 method for class 'sbh'
plot(x,
main = NULL,
proj = c(1,2),
steps = 1:x$cvfit$cv.nsteps,
pch = 16,
cex = 0.5,
col = c(1,2),
boxes = TRUE,
asp = NA,
col.box = rep(2,length(steps)),
lty.box = rep(2,length(steps)),
lwd.box = rep(1,length(steps)),
add.caption.box = boxes,
text.caption.box = paste("Step: ", steps, sep=""),
pch.group = c(1,1),
cex.group = c(1,1),
col.group = c(3,4),
add.caption.group = ifelse(test = x$cvarg$peelcriterion == "grp",
yes = TRUE,
no = FALSE),
text.caption.group = levels(x$groups),
device = NULL,
file = "Scatter Plot",
path = getwd(),
horizontal = FALSE,
width = 5,
height = 5, ...)

x 
Object of class 
main 

proj 

steps 

pch 

cex 

col 

boxes 

asp 

col.box 

lty.box 

lwd.box 

add.caption.box 

text.caption.box 

pch.group 

cex.group 

col.group 

add.caption.group 

text.caption.group 

device 
Graphic display device in { 
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. 
Use graphical parameter asp=1
for a plotting a proportional scatter plot on the graphical device
with geometrically equal scales on the x and y axes. In that case, it produces a proportional
scatter plot where distances between points are represented accurately on screen. The window is set up
so that one data unit in the x direction is equal in length to one data unit in the y direction.
The two dimensions (proj
) of the projection plane in which the scatter plot is to be plotted,
must be a subset (in the large sense) of the used (selected) covariates of sbh
object x
.
If the number of used covariates in the sbh
object is zero, the scatterplot will not be plotted.
If the number of used covariates is one, the scatterplot will be plotted using the specified
covariate and an arbitrary dimension, both specified by the user.
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." jeaneudes.dazard@case.edu
"Michael Choe, M.D." mjc206@case.edu
"Michael LeBlanc, Ph.D." mleblanc@fhcrc.org
"Alberto Santana, MBA." ahs4@case.edu
"J. Sunil Rao, Ph.D." Rao@biostat.med.miami.edu
Maintainer: "JeanEudes Dazard, Ph.D." jeaneudes.dazard@case.edu
Dazard JE. and Rao J.S. (2018). "Variable Selection Strategies for HighDimensional Survival Bump Hunting using Recursive Peeling Methods." (in prep).
Rao J.S., Huilin Y. and Dazard JE. (2018). "Disparity Subtyping: Bringing Precision Medicine Closer to Disparity Science." (in prep).
DiazPachon D.A., Saenz J.P., Dazard JE. and Rao J.S. (2018). "Mode Hunting through Active Information." (in press).
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. (2017). "Semismooth Newton Coordinate Descent Algorithm for ElasticNet Penalized Huber Loss Regression and Quantile Regression." J. Comp Graph. Statistics, 26(3):547557.
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.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.