F
Francis K. C. Hui
Researcher at Australian National University
Publications - 85
Citations - 5107
Francis K. C. Hui is an academic researcher from Australian National University. The author has contributed to research in topics: Latent variable & Random effects model. The author has an hindex of 22, co-authored 73 publications receiving 3947 citations. Previous affiliations of Francis K. C. Hui include Commonwealth Scientific and Industrial Research Organisation & Hobart Corporation.
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Journal ArticleDOI
The arcsine is asinine: the analysis of proportions in ecology
TL;DR: It is argued that the arcsine transform should not be used in either binomial or non-binomial data, and the logit transformation is proposed as an alternative approach to address these issues.
Journal ArticleDOI
Plant functional traits have globally consistent effects on competition
Georges Kunstler,Georges Kunstler,Daniel S. Falster,David A. Coomes,Francis K. C. Hui,Robert M. Kooyman,Robert M. Kooyman,Daniel C. Laughlin,Lourens Poorter,Mark C. Vanderwel,Ghislain Vieilledent,S. Joseph Wright,Masahiro Aiba,Christopher Baraloto,Christopher Baraloto,John P. Caspersen,J. Hans C. Cornelissen,Sylvie Gourlet-Fleury,Marc Hanewinkel,Bruno Hérault,Jens Kattge,Hiroko Kurokawa,Yusuke Onoda,Josep Peñuelas,Hendrik Poorter,María Uriarte,Sarah J. Richardson,Paloma Ruiz-Benito,Paloma Ruiz-Benito,I-Fang Sun,Göran Ståhl,Nathan G. Swenson,Jill Thompson,Bertil Westerlund,Christian Wirth,Miguel A. Zavala,Hongcheng Zeng,Jess K. Zimmerman,Niklaus E. Zimmermann,Mark Westoby +39 more
TL;DR: Traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies.
Journal ArticleDOI
So Many Variables: Joint Modeling in Community Ecology.
David I. Warton,F. Guillaume Blanchet,Robert B. O'Hara,Otso Ovaskainen,Otso Ovaskainen,Sara Taskinen,Steven C. Walker,Francis K. C. Hui +7 more
TL;DR: This work demonstrates the potential of a new class of multivariate models for ecology to specify a statistical model for abundances jointly across many taxa, to simultaneously explore interactions across taxa and the response of abundance to environmental variables, and discusses recent computation tools and future directions.
Journal ArticleDOI
A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels
Anna Norberg,Nerea Abrego,Nerea Abrego,F. Guillaume Blanchet,Frederick R. Adler,Barbara J. Anderson,Jani Anttila,Miguel B. Araújo,Miguel B. Araújo,Miguel B. Araújo,Tad A. Dallas,David B. Dunson,Jane Elith,Scott D. Foster,Richard Fox,Janet Franklin,William Godsoe,Antoine Guisan,Bob O'Hara,Nicole A. Hill,Robert D. Holt,Francis K. C. Hui,Magne Husby,John Atle Kålås,Aleksi Lehikoinen,Miska Luoto,Heidi K. Mod,Graeme Newell,Ian Renner,Tomas Roslin,Tomas Roslin,Janne Soininen,Wilfried Thuiller,Jarno Vanhatalo,David I. Warton,Matt White,Niklaus E. Zimmermann,Dominique Gravel,Otso Ovaskainen,Otso Ovaskainen +39 more
TL;DR: This work compared the predictive performance of 33 variants of 15 widely applied and recently emerged species distribution model approaches in the context of multispecies data, including both joint SDMs that model multiple species together, and stacked SDM that model each species individually combining the predictions afterward.
Journal ArticleDOI
boral – Bayesian Ordination and Regression Analysis of Multivariate Abundance Data in r
TL;DR: Boral as mentioned in this paper is a package available on cran for model-based analysis of multivariate abundance data, with estimation performed using Bayesian Markov chain Monte Carlo methods, incorporating latent variables as a parsimonious method of modelling between species correlation.