# warnProb: Calculate posterior probability of the weaning parameters In WARN: Weaning Age Reconstruction with Nitrogen Isotope Analysis

## Description

`warnProb` calculate posterior probabilities under a given class `"warn"` object and a given parameter range.

## Usage

 ```1 2``` ```## Default S3 method: warnProb(object, weaning.par = "age", range.x, range.y = NA) ```

## Arguments

 `object` an object of class `"warn"`. `weaning.par` character for the intended weanig parameter. The allowed values are `"age"` (the default), `"enrich"`, and `"wnfood"`. `range.x, range.y` numeric vectors of length 2, giving the range of the intended weanig parameters. For example, `range.x` corresponds to the age at the start of weaning if `weaning.par = "age"`. `range.y` is used only if `weaning.par = "age"`, and corresponds to the age at the end of weaning. Fractional point lower than e-002 is rounded.

## Details

`warnProb` calculates posterior probability of the weaning parameter that ranges between designated range. Parameter distribution is represented as the product of kernel density estimation performed in `warn`. Weaning ages are estimated from two-dimensional probability distribution, and nitrogen isotope ratios (d15Ns) of enrichment factor and weaning food derived collagen are from one-dimensional.

## Value

`warnProb` returns an object of `class` `"warnProb"` which is a subclass of `"warn"`.
The functions `summary` and `plot` are used to obtain and indicate a summary and figure of the results, respectively.
An object of class `"warnProb"` at least has following list components in addition to those succeeded from `"warn"`:

 `probability` posterior probability of parameter that range between the designated range. `range` a vector giving the range of the intended weanig parameter. `weaning.par` a character indicating the weaning parameter used.

## Author(s)

Takumi Tsutaya developed this model.

## 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.

`WARN`, `warn`, `warnCI`, `summary.warnProb`, `plot.warnProb`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30``` ```## Data from the Lerna population. nonadult <- subset(lerna, lerna\$age <= 10) adult <- subset(lerna, lerna\$age > 17) female <- subset(adult, adult\$sex == "f") ## Calculate maximum density estimators using ABC. warn.lerna <- warn( age = nonadult\$age, d15N = nonadult\$d15N, female.mean = mean(female\$d15N), num.particle = 500, female.sd = sd(female\$d15N), prior = c(0.2, 0.5, 1.6, 0.5, 2.5, 0.5, 8.1, 0.5), tolerances = c(1.5, 0.7)) ## Calculate probabilities for a given parameter range. warnprob.age <- warnProb(warn.lerna, "age", c(0.0, 1.1), c(0.8, 2.3)) warnprob.enrich <- warnProb(warn.lerna, "enrich", c(1.5, 3.5)) warnprob.wnfood <- warnProb(warn.lerna, "wnfood", c(7.3, 8.8)) ## Indicate summary. summary(warnprob.age) summary(warnprob.enrich) ## Plot. plot(warnprob.age) plot(warnprob.wnfood) ## Plot with image. plot(warnprob.age, is.image = TRUE) ```