View source: R/autoplot.clustcurves.R
autoplot.clustcurves | R Documentation |
clustcurves
objects with ggplot2 graphicsUseful for drawing the estimated functions grouped by color and the centroids (mean curve of the curves pertaining to the same group).
## S3 method for class 'clustcurves' autoplot( object = object, groups_by_colour = TRUE, centers = FALSE, conf.int = FALSE, censor = FALSE, xlab = "Time", ylab = "Survival", interactive = FALSE, ... )
object |
Object of |
groups_by_colour |
A specification for the plotting groups by color. |
centers |
Draw the centroids (mean of the curves pertaining to the
same group) into the plot. By default it is |
conf.int |
Only for survival curves. Logical flag indicating whether to plot confidence intervals. |
censor |
Only for survival curves. Logical flag indicating whether to plot censors. |
xlab |
A title for the |
ylab |
A title for the |
interactive |
Logical flag indicating if an interactive plot with plotly is produced. |
... |
Other options. |
See help page of the function autoplot.survfit
.
A ggplot object, so you can use common features from ggplot2 package to manipulate the plot.
Nora M. Villanueva and Marta Sestelo.
library(survival) library(clustcurv) library(condSURV) library(ggplot2) library(ggfortify) # Survival data(veteran) data(colonCS) cl2 <- ksurvcurves(time = veteran$time, status = veteran$status, x = veteran$celltype, k = 2, algorithm = "kmeans") autoplot(cl2) autoplot(cl2, groups_by_colour = FALSE) autoplot(cl2, centers = TRUE) # Regression r2 <- kregcurves(y = barnacle5$DW, x = barnacle5$RC, z = barnacle5$F, k = 2, algorithm = "kmeans") autoplot(r2) autoplot(r2, groups_by_colour = FALSE) autoplot(r2, groups_by_colour = FALSE, interactive = TRUE) autoplot(r2, centers = TRUE) colonCSm <- data.frame(time = colonCS$Stime, status = colonCS$event, nodes = colonCS$nodes) table(colonCSm$nodes) colonCSm$nodes[colonCSm$nodes == 0] <- NA colonCSm <- na.omit(colonCSm) colonCSm$nodes[colonCSm$nodes >= 10] <- 10 table(colonCSm$nodes) # ten levels res <- survclustcurves(time = colonCSm$time, status = colonCSm$status, x = colonCSm$nodes, algorithm = "kmeans", nboot = 20) autoplot(res) autoplot(res, groups_by_colour = FALSE) autoplot(res, centers = TRUE)
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