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plot.warn

Plot for posterior weaning parameters


Description

plot.warn is a plotting utile for quick visualization of the result of weaning age reconstruction from an object of class "warn". The measured and modeled bone collagen nitrogen isotope ratios (d15Ns) are plotted ageinst estimated ages.

Usage

## S3 method for class 'warn'
plot(x, hline.female = TRUE, hline.adult = FALSE, 
  adult.mean = NA, adult.sd = 0,
  is.legend = TRUE, is.female = TRUE, plot = TRUE, ...)

Arguments

x

an object of class "warn" generated by warn.

hline.female, hline.adult

logical; if TRUE, horizontal dotted lines indicating one standard deviation ranges of adult females and all adults are plotted on the figure; the default is TRUE for female and FALSE for adult.

adult.mean

the mean d15N of all adults, an optional single value.

adult.sd

the one standard deviation of all adult d15N, an optional single value. Utilized later in plot.warn.

is.legend

logical; if TRUE (the default), legend is plotted on the figure.

is.female

logical; if TRUE (the default), female mean d15N is plotted on the figure.

plot

logical; if TRUE (the default), a figure is plotted, otherwise a list of d15N changes in modeled bone and modeled diet is returned.

...

additional arguments passed to plot.

Details

The following three results on d15N are plotted against age, the original measured ratios of non-adult bone collagen (Measured d15N), modeled ratios of non-adult bone collagen (Modeled d15N), and modeled ratios of collagen synthesized entirely from consumed foods in the last half year (Modeld diet). These results are calculated in warn. Mean d15Ns of adult females and all adults can also be plotted.

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.

See Also

Examples

## See ?warn for examples.

WARN

Weaning Age Reconstruction with Nitrogen Isotope Analysis

v1.2-4
GPL (>= 3)
Authors
Takumi Tsutaya
Initial release
2019-10-18

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