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    A Simple Monotone Process with Application to Radiocarbon-Dated Depth Chronologies


    Haslett, John and Parnell, Andrew (2008) A Simple Monotone Process with Application to Radiocarbon-Dated Depth Chronologies. Journal of the Royal Statistical Society Series C: Applied Statistics, 57 (4). pp. 399-418. ISSN 0035-9254

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    Abstract

    Summary. We propose a new and simple continuous Markov monotone stochastic process and use it to make inference on a partially observed monotone stochastic process. The process is piecewise linear, based on additive independent gamma increments arriving in a Poisson fashion. An independent increments variation allows very simple conditional simulation of sample paths given known values of the process. We take advantage of a reparameterization involving the Tweedie distribution to provide efficient computation. The motivating problem is the establishment of a chronology for samples taken from lake sediment cores, i.e. the attribution of a set of dates to samples of the core given their depths, knowing that the age–depth relationship is monotone. The chronological information arises from radiocarbon (14C) dating at a subset of depths. We use the process to model the stochastically varying rate of sedimentation.

    Item Type: Article
    Keywords: Compound Poisson–gamma distribution; Monotone processes; Radiocarbon dating; Tweedie distribution;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 19124
    Identification Number: https://doi.org/10.1111/j.1467-9876.2008.00623.x
    Depositing User: Andrew Parnell
    Date Deposited: 30 Oct 2024 13:01
    Journal or Publication Title: Journal of the Royal Statistical Society Series C: Applied Statistics
    Publisher: Royal Statistical Society
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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