plotcredibility {bamdit} | R Documentation |
Generic plot function for metadiag object in bamdit
Description
This function plots the observe data in the ROC (Receiving Operating Characteristics) space with the posterior credibility contours.
Usage
plotcredibility(
x,
parametric.smooth = TRUE,
level = c(0.5, 0.75, 0.95),
limits.x = c(0, 1),
limits.y = c(0, 1),
color.line = "red",
color.data.points = "blue",
title = paste("Posterior Credibility Contours (50%, 75% and 95%)"),
...
)
Arguments
x |
The object generated by the metadiag function. |
parametric.smooth |
Indicates if the predictive curve is a parametric or non-parametric. |
level |
Credibility levels of the predictive curve. If parametric.smooth = FALSE, then the probability levels are estimated from the nonparametric surface. |
limits.x |
Numeric vector of length 2 specifying the x-axis limits. The default value is c(0, 1). |
limits.y |
Numeric vector of length 2 specifying the x-axis limits. The default value is c(0, 1). |
color.line |
Color of the predictive contour line. |
color.data.points |
Color of the data points. |
title |
Optional parameter for setting a title in the plot. |
... |
... |
See Also
Examples
## Not run:
library(bamdit)
data("glas")
glas.t <- glas[glas$marker == "Telomerase", 1:4]
glas.m1 <- metadiag(glas.t, # Data frame
re = "normal", # Random effects distribution
re.model = "DS", # Random effects on D and S
link = "logit", # Link function
sd.Fisher.rho = 1.7, # Prior standard deviation of correlation
nr.burnin = 1000, # Iterations for burnin
nr.iterations = 10000, # Total iterations
nr.chains = 2, # Number of chains
r2jags = TRUE) # Use r2jags as interface to jags
plotcredibility(glas.m1, # Fitted model
level = c(0.5, 0.75, 0.95), # Credibility levels
parametric.smooth = TRUE) # Parametric curve
## End(Not run)
[Package bamdit version 3.4.1 Index]