IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/ntz72.html
   My bibliography  Save this paper

Lexis Surface Visualisation Workflow

Author

Listed:
  • Minton, Jonathan

Abstract

This project describes how Lexis surface visualisations can be integrated into a broader research workflow for first learning about, and then developing and testing model specifications, as they relate to population data.

Suggested Citation

  • Minton, Jonathan, 2017. "Lexis Surface Visualisation Workflow," OSF Preprints ntz72, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:ntz72
    DOI: 10.31219/osf.io/ntz72
    as

    Download full text from publisher

    File URL: https://osf.io/download/59957438594d900259511165/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/ntz72?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Minton, Jonathan, 2017. "The Shape of the Troubles: Visualising and modelling conflict-attributable trends in mortality in young adult males in Northern Ireland," OSF Preprints hqd95, Center for Open Science.
    2. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    3. Andrew Bell & Kelvyn Jones, 2014. "Another 'futile quest'? A simulation study of Yang and Land's Hierarchical Age-Period-Cohort model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(11), pages 333-360.
    4. Jonas Schöley & Frans Willekens, 2017. "Visualizing compositional data on the Lexis surface," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 36(21), pages 627-658.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:osf:osfxxx:ntz72_v1 is not listed on IDEAS
    2. Vinícius Diniz Mayrink & Renato Valladares Panaro & Marcelo Azevedo Costa, 2021. "Structural equation modeling with time dependence: an application comparing Brazilian energy distributors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(2), pages 353-383, June.
    3. Ilya Kashnitsky & José Manuel Aburto, 2019. "Geofaceting: Aligning small-multiples for regions in a spatially meaningful way," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(17), pages 477-490.
    4. Katie Wilson & Jon Wakefield, 2022. "A probabilistic model for analyzing summary birth history data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(11), pages 291-344.
    5. Thomas C. McHale & Claudia M. Romero-Vivas & Claudio Fronterre & Pedro Arango-Padilla & Naomi R. Waterlow & Chad D. Nix & Andrew K. Falconar & Jorge Cano, 2019. "Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia," IJERPH, MDPI, vol. 16(10), pages 1-21, May.
    6. Peter Congdon, 2010. "A multiple indicator, multiple cause method for representing social capital with an application to psychological distress," Journal of Geographical Systems, Springer, vol. 12(1), pages 1-23, March.
    7. Renato Assunção & Carl Schmertmann & Joseph Potter & Suzana Cavenaghi, 2005. "Empirical bayes estimation of demographic schedules for small areas," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 537-558, August.
    8. Peter Congdon, 2014. "Estimating life expectancies for US small areas: a regression framework," Journal of Geographical Systems, Springer, vol. 16(1), pages 1-18, January.
    9. Shota Homma & Daisuke Murakami & Shinya Hosokawa & Koji Kanefuji, 2025. "Introduction risk of fire ants through container cargo in ports: Data integration approach considering a logistic network," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-15, February.
    10. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    11. Liliya Leopold & Thomas Leopold, 2016. "Education and Health across Lives and Cohorts: A Study of Cumulative Advantage in Germany," SOEPpapers on Multidisciplinary Panel Data Research 835, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. Chen, Yewen & Chang, Xiaohui & Luo, Fangzhi & Huang, Hui, 2023. "Additive dynamic models for correcting numerical model outputs," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    13. Dani Gamerman & Ajax R. B. Moreira, 2015. "Multivariate Spatial Regression Models," Discussion Papers 0116, Instituto de Pesquisa Econômica Aplicada - IPEA.
    14. Jamie M. Madden & Simon More & Conor Teljeur & Justin Gleeson & Cathal Walsh & Guy McGrath, 2021. "Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland," IJERPH, MDPI, vol. 18(12), pages 1-16, June.
    15. Peter Congdon, 2020. "Geographical Aspects of Recent Trends in Drug-Related Deaths, with a Focus on Intra-National Contextual Variation," IJERPH, MDPI, vol. 17(21), pages 1-18, November.
    16. Maciej Beręsewicz & Dagmara Nikulin, 2018. "Informal employment in Poland: an empirical spatial analysis," Spatial Economic Analysis, Taylor & Francis Journals, vol. 13(3), pages 338-355, July.
    17. Zhu, Dongping & Huang, Xiaogang & Ding, Zhixia & Zhang, Wei, 2024. "Estimation of wind turbine responses with attention-based neural network incorporating environmental uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    18. Miriam Marco & Enrique Gracia & Antonio López-Quílez & Marisol Lila, 2021. "The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach," IJERPH, MDPI, vol. 18(10), pages 1-14, May.
    19. Shreosi Sanyal & Thierry Rochereau & Cara Nichole Maesano & Laure Com-Ruelle & Isabella Annesi-Maesano, 2018. "Long-Term Effect of Outdoor Air Pollution on Mortality and Morbidity: A 12-Year Follow-Up Study for Metropolitan France," IJERPH, MDPI, vol. 15(11), pages 1-8, November.
    20. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    21. Ying C. MacNab, 2018. "Rejoinder on: Some recent work on multivariate Gaussian Markov random fields," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 554-569, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:ntz72. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.