Calculate posterior probability of the weaning parameters
warnProb
calculate posterior probabilities under a given class "warn"
object and a given parameter range.
## Default S3 method: warnProb(object, weaning.par = "age", range.x, range.y = NA)
object |
an object of class |
weaning.par |
character for the intended weanig parameter. The allowed values are |
range.x, range.y |
numeric vectors of length 2, giving the range of the intended weanig parameters. For example, |
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.
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. |
Takumi Tsutaya developed this model.
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.
## 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, 0.2, 1.6, 0.2, 2.5, 0.2, 8.1, 0.2, 0, 0.7), 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)
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