BHPMF - a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography

Global Ecology and Biogeography

Volumn 24, Issue 12, 2015, Pages 1510-1521

  Schrodt, Franziska ^a,b,c   Kattge, Jens ^a,b   Shan, Hanhuai ^d,e   Fazayeli, Farideh ^d   Joswig, Julia ^a   Banerjee, Arindam ^d   Reichstein, Markus ^a   Bönisch, Gerhard ^a   Díaz, Sandra ^f   Dickie, John ^g   Gillison, Andy ^h   Karpatne, Anuj ^d   Lavorel, Sandra ⁱ   Leadley, Paul ^j   Wirth, Christian B ^b,k   Wright, Ian J ^l   Wright, S Joseph ^m   Reich, Peter B ^c,n  

^a MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY   (Germany)

^b GERMAN CENTRE FOR INTEGRATIVE BIODIVERSITY RESEARCH IDIV HALLE JENA LEIPZIG   (Germany)

^c UNIVERSITY OF MINNESOTA   (United States)

^d University of Minnesota   (United States)

^e MICROSOFT   (United States)

^f UNIVERSIDAD NACIONAL DE CÓRDOBA   (Argentina)

^g ROYAL BOTANIC GARDENS   (United Kingdom)

^h Center for Biodiversity Management   (Australia)

ⁱ CNRS   (France)

^j UNIVERSITÉ PARIS SUD   (France)

^k UNIVERSITY OF LEIPZIG   (Germany)

^l MACQUARIE UNIVERSITY   (Australia)

^m SMITHSONIAN TROPICAL RESEARCH INSTITUTE   (Panama)

ⁿ WESTERN SYDNEY UNIVERSITY   (Australia)

more..

Author keywords

Bayesian hierarchical model; Gap filling; Imputation; Machine learning; Matrix factorization; PFT; Plant functional trait; Sparse matrix; Spatial extrapolation; TRY

Indexed keywords

BAYESIAN ANALYSIS; BIOGEOGRAPHY; MACHINE LEARNING; MACROECOLOGY; NUMERICAL MODEL; PREDICTION;

EID: 84945915645     PISSN: 1466822X     EISSN: 14668238     Source Type: Journal    
DOI: 10.1111/geb.12335     Document Type: Article

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