bamdit (version 3.4.4)

plotcredibility: 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

metadiag.

Examples

if (FALSE) {
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
}