# plot.npsurv: Plot Functions for Nonparametric Survival Estimation In npsurv: Nonparametric Survival Analysis

## Description

`plot.npsurv` and `plot.idf` are wrapper functions that call either `plotsurvidf` or `plotgradidf`.

`plotsurvidf` plots the survival function of the nonparametric maximum likelihood estimate (NPMLE).

`plotgradidf` plots the gradient function of the NPMLE.

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```## S3 method for class 'npsurv' plot(x, ...) ## S3 method for class 'idf' plot(x, data, fn=c("surv","grad"), ...) plotsurvidf(f, style=c("box","uniform","left","right","midpoint"), xlab="Time", ylab="Survival Probability", col="blue3", fill=0, add=FALSE, lty=1, lty.inf=2, xlim, ...) plotgradidf(f, data, w=1, col1="red3", col2="blue3", xlab="Survival Time", ylab="Gradient", xlim, ...) ```

## Arguments

 `x` an object of class `npsurv` (i.e., an output of function `npsurv`) or an object of class `idf`. `fn` either "surv" or "grad", to indicate plotting either the survival or the gradient function. `f` an object of class `idf`. `style` for how to plot the survival function on a "maximal intersection interval": = `box`, plot a rectangle, which shows the uncertainty of probability allocation within the interval; = `uniform`, treat it as a uniform distribution and hence the diagonal line of the rectangle is plotted; = `left`, plot only the left side of the rectangle; = `right`, plot only the right side of the rectangle; = `midpoint`, plot a vertical line at the midpoint of the interval. `xlab, ylab` x- or y-axis label. `add` = `TRUE`, adds the curve to the existing plot; = `FALSE`, plots the curve in a new one. `col` color for all line segments, including box/rectangle borders. `fill` color for filling a box/rectangle. By default, a lighter semi-transparent color is used. `lty` line type `lty.inf` line type for the rectangle that may extend to infinity. `data` vector or matrix that stores observations, or an object of class `icendata`. `w` additional weights/multiplicities of the observations stored in `x`. `col1` color for drawing maximal intersection intervals allocated with positive probabilities. `col2` color for drawing all gradients and the maximal intersection intervals allocated with zero probabilities. `xlim` x-coordinate limit points. `...` arguments for other graphical parameters (see `par`).

## Details

`plotsurvidf` by default chooses a less saturated color for `fill` than `col`.

`plotgradidf` plots gradient values as vertical lines located as the left endpoints of the maximal intersection intervals. Each maximal intersection interval is plotted as a wider line on the horizontal zero-gradient line, with a circle to represent the open left endpoint of the interval and a solid point the closed right endpoint of the interval. The maximal intersection intervals allocated with positive probabilities have zero gradients, and hence no vertical lines are drawn for them.

## Author(s)

Yong Wang <[email protected]>

## References

Wang, Y. (2008). Dimension-reduced nonparametric maximum likelihood computation for interval-censored data. Computational Statistics & Data Analysis, 52, 2388-2402.

`icendata`, `idf`, `npsurv`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```data(ap) plot(r<-npsurv(ap)) # survival function plot(r\$f, ap, fn="g") # all gradients virtually zeros. data(cancer) cancerRT = with(cancer, cancer[group=="RT",1:2]) plot(rt<-npsurv(cancerRT), xlim=c(0,60)) # survival of RT cancerRCT = with(cancer, cancer[group=="RCT",1:2]) plot(rct<-npsurv(cancerRCT), add=TRUE, col="green3") # survival of RCT ## as uniform dististrbutions. plot(rt, add=TRUE, style="uniform", col="blue3") plot(rct, add=TRUE, style="uniform", col="green3") ## plot gradients; must supply data plot(rt, cancerRT, fn="g") # for group RT plotgradidf(rct\$f, cancerRCT) # or, for group RCT ```