Through a filter, darkly: population size estimation, systematic error, and random error in radiocarbon-supported demographic temporal frequency analysis. (January 2015)

• Record Type: Journal Article
• Authors: Brown, William A.
• Is Part Of: Journal of archaeological science. Volume 53(2015:Jan.)
• Page Start: 133
• Page End: 147
• Publication Date: 2015-01
• Subjects: Archaeological demography -- Paleontology -- Temporal frequency analysis -- Radiocarbon age estimation -- Monte Carlo simulation; dTFA demographic temporal frequency analysis -- LLN Law of Large Numbers -- MC Monte Carlo -- MRT middle range theory -- tfd a sample temporal frequency distribution -- TFD a theoretical temporal frequency distribution, expressed as a probability distribution, from which tfds may be sampled -- spd summed probability distribution; Archaeology -- Periodicals; Archéologie -- Périodiques; 930.1
• DOI: 10.1016/j.jas.2014.10.013
• Languages: English
• ISSNs: 0305-4403

Abstract

Abstract: Archaeologists are increasingly concerned that the non-linear relationship between the calendric and radiocarbon timelines may introduce anomalous structures into radiocarbon-supported temporal frequency distributions ( tfd s) – time series data describing temporal fluctuations in the frequency of archaeological, paleontological, or other geological deposits. This concern emphasizes a need for improved middle range theory on tfd formation, addressing the interaction between several stochastic processes. This paper outlines a Monte Carlo simulation designed to explore the influence of several variables on tfd morphology, including the nonlinear calendric-to-radiocarbon age relationship. The results indicate that this non-linear relationship entails greater variance between identically generated tfd s over some temporal intervals than others but does not predictably lead to tfd peaks over these intervals as previously suggested. Additional variance between identically generated tfd s results from small sample sizes and high values in the underlying TFD . Smoothing the tfd is a solution not only to calibration curve interference but also to sample size-dependent sampling error. Highlights: Monte Carlo simulation is used as a tool for actualistic paleodemographic research. Stochastic processes affect temporal frequency distribution ( tfd ) formation. Calibration interference affects stability between identically generated tfd s. Kernel density estimation mitigates calibration interference and sampling error.