Francis K. C. Hui

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The arcsine square root transformation has long been standard procedure when analyzing proportional data in ecology, with applications in data sets containing binomial and non-binomial response variables. Here, we argue that the arcsine transform should not be used in either circumstance. For binomial data, logistic regression has greater interpretability(More)
Most plant species have a range of traits that deter herbivores. However, understanding of how different defences are related to one another is surprisingly weak. Many authors argue that defence traits trade off against one another, while others argue that they form coordinated defence syndromes. We collected a dataset of unprecedented taxonomic and(More)
Technological advances have enabled a new class of multivariate models for ecology, with the potential now 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. Joint models can be used for several purposes of interest to(More)
10 The adaptive lasso is a commonly applied penalty for variable selection in regression mod11 eling. Like all penalties though, its performance depends critically on the choice of tuning 12 parameter. One method for choosing the tuning parameter is via information criteria, such as 13 those based on AIC and BIC. However, these criteria were developed for(More)
Species distribution models (SDMs) are an important tool for studying the patterns of species across environmental and geographic space. For community data, a common approach involves fitting an SDM to each species separately, although the large number of models makes interpretation difficult and fails to exploit any similarities between individual species(More)
February 19, 2015 Title Bayesian Ordination and Regression AnaLysis Version 0.6 Date 2014-12-12 Author Francis K.C. Hui Maintainer Francis Hui <> Description Bayesian approaches for analyzing multivariate data in ecology. Estimation is performed using Markov Chain Monte Carlo (MCMC) methods via JAGS. Three types of models may be fitted: 1)(More)
Dormancy and germination requirements determine the timing and magnitude of seedling emergence, with important consequences for seedling survival and growth. Physiological dormancy is the most widespread form of dormancy in flowering plants, yet the seed ecology of species with this dormancy type is poorly understood in fire-prone vegetation. The role of(More)