surv.convert: Convert simulated mortality data to survivorship format.
In davidcorton/archSeries: Tools for Chronological Uncertainty in Archaeology

Description Usage Arguments Value Examples

Takes simulated frequencies for a series of ordinal classes and calculates survivorship across that series. Intended for mortality data. Survivorship currently defined as proportion surviving to *end* of given class; in future plan to add an argument allowing this to be set to *start* of class, as is standard practice in human demographics.

1 2	surv.convert(mortality, field.list = NULL, quant.list = c(0.025, 0.25, 0.5, 0.75, 0.975))

`mortality`	Output from a date.simulate, dummy.simulate, or freq.simulate call: either a data table with columns 'bin', 'bin.no' and 'rep.no' (plus at least one column of frequencies) or a list whose first item is such a data table.
`field.list`	Character vector of columns in 'mortality' which contain the mortality data to convert. Defaults to NULL, in which case all frequency columns are used.
`quant.list`	Numeric vector of quantiles to be calculated in a summary table. Defaults to c(0.025,0.25,0.5,0.75,0.975).

A list with two named elements: "full" is a long-format data table with at least four named columns: 'rep.no', integer specifying simulation run; 'bin', character specifying chronological bin in terms of date range; 'bin.no' integer specifying number of bin, counting from earliest; then for each input frequency column a column called 'survive.[input column name], giving survivorship (out of 1) to the end of the given bin in the given simulation run. "summary" is a second long format data table with four named columns: 'bin', as above; 'V1', the relevant value for the given bin at a given quantile; 'quantile', the quantile at which V1 is calculated; 'id', character specifying which column from "full" V1 is based upon.

# Simulating a sample of 50 mandibles from an ideal dairy herd model, then calculating survivorship
dairy.model <- c(0.53, 0.05, 0.03, 0.04, 0.07, 0.05, 0.04, 0.09, 0.10)
payne.breaks <- c(0, 2, 6, 12, 24, 36, 48, 2, 96, 20)
sim.ages <- dummy.simulate(50, probs=dairy.model, breaks=payne.breaks, reps=1000)
sim.survive <- surv.convert(sim.ages)