plotcredibility function

Generic plot function for metadiag object in bamdit

Generic plot function for metadiag object in bamdit

This function plots the observe data in the ROC (Receiving Operating Characteristics) space with the posterior credibility contours.

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.
  • ...: ...

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)

See Also

metadiag.

  • Maintainer: Pablo Emilio Verde
  • License: GPL (>= 2)
  • Last published: 2025-02-06

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