Journal ArticleDOI
Approximate inference in generalized linear mixed models
Norman E. Breslow,D. G. Clayton +1 more
TLDR
In this paper, generalized linear mixed models (GLMM) are used to estimate the marginal quasi-likelihood for the mean parameters and the conditional variance for the variances, and the dispersion matrix is specified in terms of a rank deficient inverse covariance matrix.Abstract:
Statistical approaches to overdispersion, correlated errors, shrinkage estimation, and smoothing of regression relationships may be encompassed within the framework of the generalized linear mixed model (GLMM). Given an unobserved vector of random effects, observations are assumed to be conditionally independent with means that depend on the linear predictor through a specified link function and conditional variances that are specified by a variance function, known prior weights and a scale factor. The random effects are assumed to be normally distributed with mean zero and dispersion matrix depending on unknown variance components. For problems involving time series, spatial aggregation and smoothing, the dispersion may be specified in terms of a rank deficient inverse covariance matrix. Approximation of the marginal quasi-likelihood using Laplace's method leads eventually to estimating equations based on penalized quasilikelihood or PQL for the mean parameters and pseudo-likelihood for the variances. Im...read more
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Modeling dominant height growth based on nonlinear mixed-effects model: a clonal Eucalyptus plantation case study
TL;DR: In this article, a nonlinear mixed-effects model was developed to represent the height growth pattern of eucalypts clonal stands from the Brazilian coastal region, which showed to be flexible, precise and accurate, generating multimorphic growth curves for different sites and clones.
Journal ArticleDOI
Seeing the trees for the leaves / oaks as mosaics for a host-specific moth
Tomas Roslin,Sofia Gripenberg,Juha-Pekka Salminen,Maarit Karonen,Robert B. O'Hara,Kalevi Pihlaja,Pertti Pulkkinen +6 more
TL;DR: The large variation observed in the performance of a specialist moth and in the physical traits of the leaves among different parts of single tree crowns refutes the image of an oak tree as an ‘island’ of internally homogeneous quality.
Journal ArticleDOI
Fast sinking (integrated weight) longlines reduce mortality of white-chinned petrels (Procellaria aequinoctialis) and sooty shearwaters (Puffinus griseus) in demersal longline fisheries
Graham Robertson,Malcolm McNeill,Neville Smith,Barbara Wienecke,Steven G. Candy,Frederique Olivier +5 more
TL;DR: Use of IW longlines and streamer lines in autoline fisheries should yield major conservation benefits to seabirds interacting with these fisheries worldwide.
Journal ArticleDOI
Évolution de l'épistémè économique et sociale : proposition d'un cadre de morale, de déontologie, d'éthique et de responsabilité pour le marketer
TL;DR: In this article, a cadre of reflexion and action articule autour des dimensions de morale, de deontologie, d'ethique and de responsabilite, dans la perspective d'une methodologie individuelle.
Journal ArticleDOI
Effects of hydroperiod and substrate properties on tree alpha diversity and composition in Amazonian floodplain forests
Rafael L. Assis,Rafael L. Assis,Florian Wittmann,Maria Teresa Fernandez Piedade,Torbjørn Haugaasen +4 more
TL;DR: It is concluded that floristic diversity and composition are more influenced by the hydroperiod than by substrate conditions, and substrate conditions become decreasingly important for increasingly flood-tolerant species.
References
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Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Book
Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI
Longitudinal data analysis using generalized linear models
Kung Yee Liang,Scott L. Zeger +1 more
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.