In community ecology studies the goal is to evaluate the effect of environmental covariates on a response variable while investigating the nature unobserved heterogeneity. We focus on onefactor mixed models in a Bayesian setting and introduce an intuitive Penalized Complexity (PC) prior to balance the variance components of the model. We start with the simple one-way anova and discuss extension to spatially structured residuals, following a Matern exponential covariance
Modelling species interactions in diverse communities traditionally requires a prohibitively large n...
International audienceModelling species distributions over space and time is one of the major resear...
1. Statistical tests partitioning community variation into environmental and spatial components have...
Lack of independence in the residuals from linear regression motivates the use of random effect mode...
none2noGeneralized linear mixed models (GLMM) represent a flexible tool to model environmental data ...
Statistics is a science that deals with variability in data. The presence of variation in natural pr...
The effectiveness and validity of applying variation partitioning methods in community ecology has b...
<p>Conditioned variables are treated as covariates and held constant whilst investigating the amount...
To understand patterns of variation in species biomass in terms of species traits and environmental ...
Varying coefficient models are useful in applications where the effect of the covariate might depend...
Varying coefficient models arise naturally as a flexible extension of a simpler model where the effe...
In this thesis, new methods are proposed for using finite mixture models to analyse multi-species da...
Covariates and traits used to model community occupancy (ψ) and detectability (p) across the landsca...
The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological d...
Understanding the mechanisms of ecological community dynamics and how they could be affected by envi...
Modelling species interactions in diverse communities traditionally requires a prohibitively large n...
International audienceModelling species distributions over space and time is one of the major resear...
1. Statistical tests partitioning community variation into environmental and spatial components have...
Lack of independence in the residuals from linear regression motivates the use of random effect mode...
none2noGeneralized linear mixed models (GLMM) represent a flexible tool to model environmental data ...
Statistics is a science that deals with variability in data. The presence of variation in natural pr...
The effectiveness and validity of applying variation partitioning methods in community ecology has b...
<p>Conditioned variables are treated as covariates and held constant whilst investigating the amount...
To understand patterns of variation in species biomass in terms of species traits and environmental ...
Varying coefficient models are useful in applications where the effect of the covariate might depend...
Varying coefficient models arise naturally as a flexible extension of a simpler model where the effe...
In this thesis, new methods are proposed for using finite mixture models to analyse multi-species da...
Covariates and traits used to model community occupancy (ψ) and detectability (p) across the landsca...
The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological d...
Understanding the mechanisms of ecological community dynamics and how they could be affected by envi...
Modelling species interactions in diverse communities traditionally requires a prohibitively large n...
International audienceModelling species distributions over space and time is one of the major resear...
1. Statistical tests partitioning community variation into environmental and spatial components have...