zooaRch (version 1.2)

mort.func: Analysis of Mortality Profiles

Description

This is a function used to conduct mortality analyses of zooarchaeological data

Usage

mort.func(mortData, labels = NULL, models = NULL, ci = 95, plot = TRUE, iter = 1000, usermod = NULL, lsize = 0.1)

Arguments

mortData

is the age-at-death dataset. This function inputs datasets composed of three columns. The first column denotes the genus; the second is the age class (this MUST be numeric) if data contains nominal age classes (e.g., 'A', 'B', 'C', etc.) these data must be converted to numbers (e.g., A = 1, B = 2, etc.).

labels

Character value indicating wether age class labels wishing to be displayed.

models

A numerical value (1-5) indiacting the models to compare the data to. Currently mort.func makes use of 5 mortality models: 1) Security (ref); 2) Milk (ref); 3) Wool (ref); 4) Catastrophic (Stiner 1990); and 5) Attritional (Stiner 1990). More models will be added soon. An option to include user's own model will also be available.

ci

Numerical value indicating desired CI level (e.g., 90, 95, 99). Defaults to 95.

plot

A logical value indicating wether user wishes an output plot. Default = TRUE.

iter

A numeric value indicating the number of bootstrap iterations. Defaults to 1000.

usermod

numeric list (see help(list)) user-specified mortality model. See example 3 below. Data must be entered as a list, else user will receive error.

lsize

A numeric value indicating the vertical spacing value in a legend.

Value

Function returns a matrix with the following components

Lower and Upper CI

typically the 97.5 and 2.5 percentile markers

Point Value

the y value on the mortality profile

Details

This function plots mortality profiles, along with Confidence Intervals using dental eruption and wear data. Optionally, plotted mortality profiles can be compared to idealized models of mortality.

References

Klein, R.G., Cruz-Uribe, K., 1983. The Analysis of Animal Bones from Archaeological Sites, University of Chicago Press, Chicago.

Stiner, M. C. 1990 The Use of Mortality Patterns in Archaeological Studies of Hominid Predatory Adaptations. Journal of Anthropological Archaeology 9:305 - 351.

Lyman, R.L., 1994. Vertebrate Taphonomy, Cambridge University Press, Cambridge.

Voorhies, M. R., 1969 Taphonomy and Population Dynamics of an Early Pliocene Vertebrate Fauna, Knox County, Nebraska. University of Wymonig Press. Contributions to Geology, Special Paper No. 1, Laramie (WY).

Reitz, E. and E. Wing 2008 Zooarchaeology. Second Edition. Cambridge University Press, Cambridge.

Examples

# Example 1: Payne 1973
 data(marjRab)

# Inspect data structure  
 head(marjRab)
 
# create age-class labels: Payne 1973 uses ageclasses A-I
 Labels <-c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I')
 mort.func(mortData=marjRab,labels=Labels, models=1:3, ci=95, plot=TRUE, iter=1000)
 
# Example 2: Garnsey Site Bison Data (from Speth 1983)
 data(speth83)

# Inspect data structure  
 head(speth83)

# create age-class labels using the 13 age classes of Speth's (1983) scheme.
 Labels <-c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)

# Use the catastrophic and attritional mortality curves (after Stiner 1990).
 mort.func(mortData=speth83,labels=Labels, models=4:5, ci=95, plot=TRUE, iter=1000)