The last decade has seen the development of a range of new statistical and computational techniques for analysing large collections of radiocarbon (14C) dates, often but not exclusively to make inferences about human population change in the past. Here we introduce rcarbon, an open-source software package for the R statistical computing language which implements many of these techniques and looks to foster transparent future study of their strengths and weaknesses. In this paper, we review the key assumptions, limitations and potentials behind statistical analyses of summed probability distribution of 14C dates, including Monte-Carlo simulation-based tests, permutation tests, and spatial analyses. Supplementary material provides a fully reproducible analysis with further details not covered in the main paper.

中文翻译：

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来自大量放射性碳日期的推论：软件和方法

在过去的十年中，一系列用于分析大量放射性碳集合的新统计和计算技术得到了发展（14C) 日期，通常但不仅限于推断过去的人口变化。这里我们介绍碳，一个用于 R 统计计算语言的开源软件包，它实现了许多这些技术，并希望促进对其优缺点的透明未来研究。在本文中，我们回顾了总概率分布统计分析背后的关键假设、局限性和潜力。14C 日期，包括基于蒙特卡罗模拟的测试、置换测试和空间分析。补充材料提供了完全可重复的分析，其中更多细节未在主要论文中涵盖。