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Last data update: 2014.03.03

R: Thresholds and density plot (three-state setting)

plot.thres3

R Documentation

Thresholds and density plot (three-state setting)

Description

The function provides a graphic including the three sample densities, the thresholds and their confidence intervals.

Usage

## S3 method for class 'thres3'
plot(x, bw = c("nrd0", "nrd0", "nrd0"), ci = TRUE,
  which.boot = c("norm", "perc"), col = c(1, 2, 3, 1),
  lty = c(1, 1, 1, 1, 2), lwd = c(1, 1, 1, 1),
  main = paste0("Threshold estimates", ifelse(ci, " and CIs", "")),
  xlab = "", legend = TRUE, leg.pos = "topleft", leg.cex = 1, ...)

Arguments

`x`	an object of class `thres3`.
`bw`	vector containing the bandwith for the first sample in the first position, the bandwith for the second sample in the second position and the bandwith for the third sample in the third position (to be passed to `density()`). Default, `c("nrd0", "nrd0", "nrd0")`.
`ci`	should the confidence intervals be plotted? Default, `TRUE`.
`which.boot`	in case `x` contains confidence intervals computed by bootstrapping, which one should be printed? The user can choose between `"norm"` (based on normal distribution) or `"perc"` (based on percentiles). Default, `"norm"`. This argument is ignored if parametric confidence intervals were computed.
`col`	a 4-dimensional vector containing: `col[1]`: color for the density of the first sample `col[2]`: color for the density of the second sample `col[3]`: color for the density of the third sample `col[4]`: color for the thresholds and their corresponding confidence intervals Default, `c(1, 2, 3, 1)`.
`lty`	a 5-dimensional vector containing: `lty[1]`: line type for the density of the first sample `lty[2]`: line type for the density of the second sample `lty[3]`: line type for the density of the third sample `lty[4]`: line type for the thresholds `lty[5]`: line type for the confidence intervals Default, `c(1, 1, 1, 1, 2)`.
`lwd`	a 4-dimensional vector containing: `lwd[1]`: line width for the density of the first sample `lwd[2]`: line width for the density of the second sample `lwd[3]`: line width for the density of the third sample `lwd[4]`: line width for the thresholds and their corresponding confidence intervals Default, `c(1, 1, 1, 1)`.
`legend`	logical asking if an automatic legend should be added to the graph. Default, `TRUE`.
`leg.pos`	position of the legend. Default, `"topleft"`. Ignored if `legend=FALSE`.
`leg.cex`	number that reescales the size of the legend. Ignored if `legend=FALSE`. Default, 1.
`main, xlab, ...`	further arguments to be passed to `plot()`.

Value

Estimates of the density functions for the three samples and vertical lines representing the thresholds and their confidence limits are drawn.

References

Skaltsa K, Jover L, Fuster D, Carrasco JL. (2012). Optimum threshold estimation based on cost function in a multistate diagnostic setting. Statistics in Medicine, 31:1098-1109.

Examples

set.seed(1234)
n <- 100
k1 <- rlnorm(n)
k2 <- rnorm(n, 3, 1)
k3 <- rnorm(n, 5, 1)
rho <- c(1/3, 1/3, 1/3)

# assuming trinormality
start <- c(mean(k1), mean(k3)) 
thres <- thres3(k1, k2, k3, rho, dist1="norm", dist2="norm",
                dist3="norm", start=start, ci.method="param") 
plot(thres, leg.pos="topright")

# not assuming trinormality
thres <- thres3(k1, k2, k3, rho, dist1="lnorm", dist2="norm",
                dist3="norm", ci.method="boot") 
plot(thres, leg.pos="topright", which.boot="perc")