ProportionalAgeDistribution: Proportional Distribution of Age Estimates Among Age...
In cuboideum/deadpop: Analysis of Skeletal Populations

Description Usage Arguments Details Value Note References Examples

View source: R/ProportionalAgeDistribution.R

Age-at-death estimates from skeletons are usually expressed in age spans, each delimited by a minimum and a maximum age-at-death estimate, respectively. The function divides the contribution from each individual by the number of years covered by the respective age span and assigns the resulting fraction to each year in the span. Then, it sums up these yearly contributions from individuals to determine contributions from all individuals to specified age categories. This procedure is referred to, here, as 'proportional distribution of age estimates'.

ProportionalAgeDistribution(
  minAge = NA,
  maxAge = NA,
  cats = seq(floor(min(minAge)), ceiling(max(maxAge)), 1),
  accept.empty = FALSE
)

`minAge, maxAge`	Vectors of integers specifying minimum and maximum age-at-death estimates for a series of individuals.
`cats`	A vector of breaks defining age categories. The breaks are understood as points on a time line and not as units that might be part of one of the categories they divide. If no value is defined, single years within the age range defined by `minAge` and `maxAge` are used as categories.
`accept.empty`	A boolean statement specifying whether the function should accept calls not providing age estimates, i.e. with `minAge` and `maxAge` being empty. If set to TRUE, the function will return a vector with value zero for all age categories. If set to FALSE (the default), the function will abort with an error message. Setting accept.empty to TRUE can be helpful in batch processing where empty inputs might be created by automated calculations.

Boldsen (1988) describes the reconstruction of mortality profiles. These can also be expressed as distributions of age-at-death estimates, as performed by this function.

A vector of the same length as numbers of categories (length(cats) - 1) is returned, giving the numbers of individuals that have been assigned to each age category. As individuals are distributed among several categories, these numbers might be fractions.

As minAge and maxAge refer to the same number of individuals, they have to be of identical length.

Boldsen JL. 1988. Two Methods for Reconstructing the Empirical Mortality Profile. Human Evolution 3(5):335-342.

## Age estimations for four individuals
min_x <- c(3, 14, 24, 45)
max_x <- c(5, 22, 35, 80)
x1 <- ProportionalAgeDistribution(minAge=min_x, maxAge=max_x)
sum(x1) # number of individuals represented in categories of x1
x2 <- ProportionalAgeDistribution(minAge=min_x, maxAge=max_x, cats = c(0, 20, 40, 60, 80))
sum(x2) # number of individuals represented in categories of x2
x3 <- ProportionalAgeDistribution(minAge=min_x, maxAge=max_x, cats = c(10, 20, 30, 40))
sum(x3) # number of individuals represented in categories of x3