Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Janine B. Illian"'
Publikováno v:
Methods in Ecology and Evolution, Vol 14, Iss 1, Pp 162-172 (2023)
Abstract The potential for statistical complexity in species distribution models (SDMs) has greatly increased with advances in computational power. Structurally complex models provide the flexibility to analyse intricate ecological systems and realis
Externí odkaz:
https://doaj.org/article/aa91017e84f445408b96d345d3ed99e1
Publikováno v:
PLoS ONE, Vol 16, Iss 12 (2021)
Objectives To model the risk of COVID-19 mortality in British care homes conditional on the community level risk. Methods A two stage modeling process (“doubly latent”) which includes a Besag York Mollie model (BYM) and a Log Gaussian Cox Process
Externí odkaz:
https://doaj.org/article/825229dea4bc43d2b699ce8a1163522f
Publikováno v:
Methods in Ecology and Evolution. 14:162-172
1. The potential for statistical complexity in species distribution models (SDMs) has greatly increased with advances in computational power. Structurally complex models provide the flexibility to analyse intricate ecological systems and realisticall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f27046f040b45007a4a005de794e7e8
https://doi.org/10.1111/2041-210x.13957
https://doi.org/10.1111/2041-210x.13957
Autor:
Iosu Paradinas, Janine B Illian, Alexandre Alonso-Fernändez, Maria Grazia Pennino, Sophie Smout
IP would like to thank the European Commission for the funding (GAP-847014). IP is grateful to the MSCA fellowship that supported his research. MGP thanks the project IMPRESS (RTI2018-099868-B-I00), ERDF, Ministry of Science, Innovation, and Universi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cbed8f92e3bd17fbd7b9f003ce3070c
https://hdl.handle.net/10023/27642
https://hdl.handle.net/10023/27642
This paper proposes a two-stage estimation approach for a spatial misalignment scenario that is motivated by the epidemiological problem of linking pollutant exposures and health outcomes. We use integrated nested Laplace approximation method to esti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbf1dcafc44b6ae2436546cb56d774cf
https://hdl.handle.net/10023/27438
https://hdl.handle.net/10023/27438
Publikováno v:
Wiley StatsRef: Statistics Reference Online. :1-6
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f20fd2f13c9e99b4da0a99da0f11bbc
https://doi.org/10.1002/9781118445112.stat08250
https://doi.org/10.1002/9781118445112.stat08250
Autor:
Wei Zhang, Joseph D. Chipperfield, Janine B. Illian, Pierre Dupont, Cyril Milleret, Perry de Valpine, Richard Bischof
Publikováno v:
Ecology
e3887
e3887
Spatial capture–recapture (SCR) is now routinely used for estimating abundance and density of wildlife populations. A standard SCR model includes sub-models for the distribution of individual activity centers (ACs) and for individual detections con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a82c733f8acf74e4dfe7543db6ab0dc1
https://hdl.handle.net/11250/3049305
https://hdl.handle.net/11250/3049305
Publikováno v:
Spatial Statistics. 29:268-288
The classical tools in spatial statistics are stationary models, like the Mat\'ern field. However, in some applications there are boundaries, holes, or physical barriers in the study area, e.g. a coastline, and stationary models will inappropriately
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bb372b3dcb46ee4e9614fb399710e9d
https://doi.org/10.1016/j.spasta.2019.01.002
https://doi.org/10.1016/j.spasta.2019.01.002
Autor:
Laura D. Williamson, Beth E. Scott, Megan Laxton, Janine B. Illian, Victoria L.G. Todd, Peter I. Miller, Kate L. Brookes
Publikováno v:
Ecological Modelling. 470:110011
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62d82c45b4f03484bb6a2cd2111462b3
https://doi.org/10.1016/j.ecolmodel.2022.110011
https://doi.org/10.1016/j.ecolmodel.2022.110011