Repository for papers, data and stuff related to the analysis of coin hoards for change points in late Antiquity/early Middle Ages in Europe.
The repository with code, paper source and data is in GitHub.
For the time being, these papers:
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We focus on the periphery of the Roman Empire, namely, Hispania or the Iberian peninsula, Analyzing Late Antiquity Shifts of Trade Regime in the Iberian Peninsula and Their Causes via Change Point Detection Methods applying change point detection to internal/external trade links created through censoring, thta is assigning link probabilites from coin hoards. The state of the repository when publishing this paper has been released as version 2.1.1.
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An extended report is published at the UGR institutional repository, "Finding changepoints in medieval European and Middle Eastern trade networks", where the "Danubian hypothesis" is proposed: The change in trade patterns before and after the changepoint suggest that the fall of the Danube as a trade route internal to the empire, as well as probable the Via Militaris that run parallel to it, totally changed the trading patterns, decreasing the number of trade links and creating economic and finally military and political change.
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For Statphys 29: "Finding changepoints in medieval Mediterranean trade networks", check the paper source as well as the paper. The file
data/links_year.rdscontains the data processed for the paper.scripts/abstract-medieval-trade.Rcontain the extracted script that generates the chart in the paper, slightly modified for the actual poster.
If you want to use the processed data and/or code in this paper, we kindly request you to cite:
@Article{complexities2020012,
AUTHOR = {Merelo-Guervós, Juan Julián},
TITLE = {Analyzing Late Antiquity Shifts of Trade Regime in the Iberian Peninsula and Their Causes via Change Point Detection Methods},
JOURNAL = {Complexities},
VOLUME = {2},
YEAR = {2026},
NUMBER = {2},
ARTICLE-NUMBER = {12},
URL = {https://www.mdpi.com/3042-6448/2/2/12},
ISSN = {3042-6448},
ABSTRACT = {History attempts to make sense of disparate information by trying to create discourse that lays a series of events with crisp cause–effect relationships in a sequence. Epochal shifts, such as the change from Antiquity to the Middle Ages, are especially complex since they involve a large number of economic, political and even religious factors which occur over long periods and that might overlap and interact through reciprocal feedback mechanisms, making this cause–effects sequence difficult to establish. In this research we adopt a data-driven and well-established methodology to identify, with quantifiable statistical precision, the moment when this shift happened, and from there arrive at its possible causes. We will use historical coin hoard data to find out whether such a shift is detected in a peripheral part of the Roman Empire, the Iberian Peninsula. To do so, we will apply different changepoint analysis methods to a time series of trade links created from that data, and conduct a retrospective analysis based on that result, analyzing the structure of the trade networks before and after the link. Thus, we progress from identifying when the shift happened to identifying where it took place, which in turn allows us to get to investigate why it happened, namely, historical events that could have caused it. This methodology can be used to analyze epochal changes in several steps using time-stamped network data, possibly finding disregarded causes or cause–effect links that could have been overlooked by qualitative methods; in this case, we have applied it to a dataset of coin hoards either found in the Iberian Peninsula or including coins minted there, finding a changepoint in the early 5th century, which, through network analysis, has been linked to a loss of trade with the area of Britannia.},
DOI = {10.3390/complexities2020012}
}
Please check out the biblio.bib file for all references.
Data was obtained from the FLAMEs database. data-raw contains
unprocessed files, data/ the files once processed, that can be used
directly.
All papers have been uploaded to this Perplexity AI model. Ask anything about it.
(c) JJ Merelo, 2025. Data and code are licensed under the Affero GPL license.