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  1. Headhunting and warfare
    evidence from Austronesia
    Autor*in: Gershman, Boris; Mumladze, Tinatin
    Erschienen: July 2023
    Verlag:  Economics, College of Arts & Sciences, American University, Washington, DC

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    VS 530
    Fernleihe:
    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Working papers / Economics, College of Arts & Sciences, American University ; 2023, 06
    Schlagworte: Austronesia; Conflict; Correlated evolution; Culture; Headhunting; Phylogeneticcomparative methods; Supernatural beliefs; Warfare
    Umfang: 1 Online-Ressource (circa 36 Seiten), Illustrationen
  2. An information-theoretic method for identifying effective treatments and policies at the beginning of a pandemic
    Autor*in: Golan, Amos; Mumladze, Tinatin; Perloff, Jeffrey M.; Wilson, Danielle
    Erschienen: 2023
    Verlag:  Department of Agricultural and Resource Economics, UC Berkeley, [Berkeley, CA]

    Background: Identifying effective treatments and policies early in a pandemic is challenging because only limited and noisy data are available, and biological processes are unknown or uncertain. Consequently, classical statistical procedures may not... mehr

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    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Fernleihe:
    keine Fernleihe

     

    Background: Identifying effective treatments and policies early in a pandemic is challenging because only limited and noisy data are available, and biological processes are unknown or uncertain. Consequently, classical statistical procedures may not work or require strong structural assumptions. An information-theoretic approach can overcome these problems and identify effective treatments and policies. The efficacy of this approach is illustrated using a study conducted at the beginning of the COVID-19 pandemic.Methods: An information-theoretic inferential approach with and without prior information was applied to the limited data available in the second month (April 24, 2020) of the COVID-19 pandemic. For comparison, a second statistical analysis used a large sample with millions of observations available at the end of the pandemic's pre-vaccination period (mid-December 2020).Results: Even with limited data, the information-theoretic estimates performed well in identifying influential factors and helped explain why death rates varied across nations. Later experiments and statistical analyses based on more recent, richer data confirm that these factors contribute to survival.Conclusions: An information-theoretic statistical technique is a robust method that can overcome the challenges of under-identified estimation problems in the early stages of medical emergencies. It can easily incorporate prior information from theory, logic, or previously observed emergencies

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: CUDARE working papers
    Schlagworte: Information-theoretic inference; COVID-19; identification; mortality
    Umfang: 1 Online-Ressource (circa 15 Seiten), Illustrationen