WARN: plot.warnProb – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

plot.warnProb

Plot for probabilities of posterior weaning parameters

Description

plot.warnProb is a plotting utile for quick visualization of the posterior weaning parameters from an object of class "warnProb". Results of kernel density estimation for the posteriors are plotted as a form of contour with designated parameter ranges.

Usage

## S3 method for class 'warnProb'
plot(x, is.legend = TRUE, is.contour = TRUE,
  is.image = FALSE, is.prior = FALSE, ...)

Arguments

`x`	an object of class `"warnProb"` generated by `warnProb`.
`is.legend`	logical; if `TRUE` (the default), legend is plotted on the figure.
`is.contour`	logical; if `TRUE` (the default), contour lines corresponding to the probabilirties are plotted with `contour`. Only used if the intended weanig parameter is weaning ages (i.e., `weaning.par = "age"` in `warnProb`).
`is.image`	logical; if `TRUE`, grid of gray-scale rectangles with color strength corresponding to the probabilirties is plotted with `image`. The default is `FALSE`, and only used if the intended weanig parameter is weaning ages (i.e., `weaning.par = "age"` in `warnProb`).
`is.prior`	logical; if `TRUE`, prior density of the paramter is also plotted with dotted line. The default is `FALSE`, and only used if the intended weanig parameter is enrichment or weaning food (i.e., `weaning.par = "enrich"` or `"wnfood"` in `warnProb`).
`...`	additional arguments passed to `plot`.

Details

Values on the contour lines indicate relative probabilities based on that of the maximum density estimator.

References

Tsutaya, T., and Yoneda, M. (2013). Quantitative reconstruction of weaning ages in archaeological human populations using bone collagen nitrogen isotope ratios and approximate Bayesian computation. PLoS ONE 8, e72327.

Examples

## See ?warnProb for examples.

WARN

Weaning Age Reconstruction with Nitrogen Isotope Analysis

v1.2-4

GPL (>= 3)

Authors

Takumi Tsutaya

Initial release

2019-10-18