This article by Christopher Bronk Ramsey discusses deposition models for chronological records, focusing on Bayesian methods to improve the accuracy and precision of age-depth models for sedimentary sequences. The paper outlines various Bayesian models implemented in the OxCal software, which allow the integration of radiocarbon and other dating information with sedimentary data to create coherent chronologies. These models are essential for interpreting palaeo-climate records and archaeological findings, as they help to account for uncertainties and provide a framework for combining different types of data. The paper begins by emphasizing the need for precise chronologies to integrate different palaeo-climate records, highlighting the challenges posed by uncertainties in dating methods. It then introduces the Bayesian approach, which allows the combination of probabilistic information to refine chronologies. The Bayesian framework is applied to incorporate both absolute and relative dating information, as well as cross-correlations between records, to build accurate models. The article details various deposition models, including the uniform deposition model, the Poisson process model, and others, each with specific assumptions about the deposition rate and the nature of uncertainties. The Poisson process model, which assumes random variation around a constant rate, is discussed in detail, along with its application to real-world scenarios such as lake sediments and ice cores. The paper also addresses the challenges of estimating the $k$ parameter, which defines the number of accumulation events per unit depth, and how this can be determined from direct measurements or dating information. The application of these models is illustrated through examples, including the analysis of varved lake sediments from Soppensee and ice core layers. The paper highlights the importance of considering uncertainties, identifying outliers, and using statistical measures to evaluate the reliability of the models. It also discusses the use of the agreement index to assess the consistency of results and the potential for further refinements in modeling deposition processes. In conclusion, the article emphasizes the importance of Bayesian methods in improving the accuracy of chronological records, enabling the integration of diverse data sources and providing a robust framework for interpreting sedimentary and archaeological sequences. The use of OxCal software facilitates the implementation of these models, allowing researchers to generate posterior probability distributions and age-depth models that account for uncertainties and provide a coherent understanding of past events.This article by Christopher Bronk Ramsey discusses deposition models for chronological records, focusing on Bayesian methods to improve the accuracy and precision of age-depth models for sedimentary sequences. The paper outlines various Bayesian models implemented in the OxCal software, which allow the integration of radiocarbon and other dating information with sedimentary data to create coherent chronologies. These models are essential for interpreting palaeo-climate records and archaeological findings, as they help to account for uncertainties and provide a framework for combining different types of data. The paper begins by emphasizing the need for precise chronologies to integrate different palaeo-climate records, highlighting the challenges posed by uncertainties in dating methods. It then introduces the Bayesian approach, which allows the combination of probabilistic information to refine chronologies. The Bayesian framework is applied to incorporate both absolute and relative dating information, as well as cross-correlations between records, to build accurate models. The article details various deposition models, including the uniform deposition model, the Poisson process model, and others, each with specific assumptions about the deposition rate and the nature of uncertainties. The Poisson process model, which assumes random variation around a constant rate, is discussed in detail, along with its application to real-world scenarios such as lake sediments and ice cores. The paper also addresses the challenges of estimating the $k$ parameter, which defines the number of accumulation events per unit depth, and how this can be determined from direct measurements or dating information. The application of these models is illustrated through examples, including the analysis of varved lake sediments from Soppensee and ice core layers. The paper highlights the importance of considering uncertainties, identifying outliers, and using statistical measures to evaluate the reliability of the models. It also discusses the use of the agreement index to assess the consistency of results and the potential for further refinements in modeling deposition processes. In conclusion, the article emphasizes the importance of Bayesian methods in improving the accuracy of chronological records, enabling the integration of diverse data sources and providing a robust framework for interpreting sedimentary and archaeological sequences. The use of OxCal software facilitates the implementation of these models, allowing researchers to generate posterior probability distributions and age-depth models that account for uncertainties and provide a coherent understanding of past events.