Search results for "Generalized linear model"
showing 10 items of 40 documents
Scale dependence of species–area relationships is widespread but generally weak in Palaearctic grasslands
2021
Questions: Species–area relationships (SARs) are fundamental for understanding biodiversity patterns and are generally well described by a power law with a constant exponent z. However, z-values sometimes vary across spatial scales. We asked whether there is a general scale dependence of z-values at fine spatial grains and which potential drivers influence it. Location: Palaearctic biogeographic realm. Methods: We used 6,696 nested-plot series of vascular plants, bryophytes and lichens from the GrassPlot database with two or more grain sizes, ranging from 0.0001 m² to 1,024 m² and covering diverse open habitats. The plots were recorded with two widespread sampling approaches (rooted presenc…
Distance decay 2.0 – a global synthesis of taxonomic and functional turnover in ecological communities
2021
AbstractUnderstanding the variation in community composition and species abundances, i.e., β-diversity, is at the heart of community ecology. A common approach to examine β-diversity is to evaluate directional turnover in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distances. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 149 datasets comprising different types of organisms and environments. We modelled an exponential distance decay for each dataset using generalized linear models and extracted r2 and slope to analyse the streng…
Risk of predation makes foragers less choosy about their food.
2017
18 pages; International audience; Animals foraging in the wild have to balance speed of decision making and accuracy of assessment of a food item's quality. If resource quality is important for maximizing fitness, then the duration of decision making may be in conflict with other crucial and time consuming tasks, such as anti-predator behaviours or competition monitoring. Individuals facing the risk of predation and/or competition should adjust the duration of decision making and, as a consequence, their level of choosiness for resources. When exposed to predation, the forager could either maintain its level of choosiness for food items but accept a reduction in the amount of food items con…
Probabilistic liver atlas construction
2017
Background Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. Results A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve p…
Bayesian dynamic modeling of time series of dengue disease case counts
2017
The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order …
Differential geometric LARS via cyclic coordinate descent method
2012
We address the problem of how to compute the coefficient path implicitly defined by the differential geometric LARS (dgLARS) method in a high-dimensional setting. Although the geometrical theory developed to define the dgLARS method does not need of the definition of a penalty function, we show that it is possible to develop a cyclic coordinate descent algorithm to compute the solution curve in a high-dimensional setting. Simulation studies show that the proposed algorithm is significantly faster than the prediction-corrector algorithm originally developed to compute the dgLARS solution curve.
Dual Extrapolation for Sparse Generalized Linear Models
2020
International audience; Generalized Linear Models (GLM) form a wide class of regression and classification models, where prediction is a function of a linear combination of the input variables. For statistical inference in high dimension, sparsity inducing regularizations have proven to be useful while offering statistical guarantees. However, solving the resulting optimization problems can be challenging: even for popular iterative algorithms such as coordinate descent, one needs to loop over a large number of variables. To mitigate this, techniques known as screening rules and working sets diminish the size of the optimization problem at hand, either by progressively removing variables, o…
Implicit differentiation for fast hyperparameter selection in non-smooth convex learning
2022
International audience; Finding the optimal hyperparameters of a model can be cast as a bilevel optimization problem, typically solved using zero-order techniques. In this work we study first-order methods when the inner optimization problem is convex but non-smooth. We show that the forward-mode differentiation of proximal gradient descent and proximal coordinate descent yield sequences of Jacobians converging toward the exact Jacobian. Using implicit differentiation, we show it is possible to leverage the non-smoothness of the inner problem to speed up the computation. Finally, we provide a bound on the error made on the hypergradient when the inner optimization problem is solved approxim…
A Widrow–Hoff Learning Rule for a Generalization of the Linear Auto-associator
1996
Abstract A generalization of the linear auto-associator that allows for differential importance and nonindependence of both the stimuli and the units has been described previously by Abdi (1988). This model was shown to implement the general linear model of multivariate statistics. In this note, a proof is given that the Widrow–Hoff learning rule can be similarly generalized and that the weight matrix will converge to a generalized pseudo-inverse when the learning parameter is properly chosen. The value of the learning parameter is shown to be dependent only upon the (generalized) eigenvalues of the weight matrix and not upon the eigenvectors themselves. This proof provides a unified framew…
Habitat preferences of edible dormouse, Glis glis italicus: implications for the management of arboreal mammals in Mediterranean forests
2015
Research on arboreal mammals living in Mediterranean forests is poor. Molecular research assessed the existence of an evolutionary significant unit in the edible dormouse populations living in south Italy, Sicily and Sardinia, and we decided to investigate the environmental factors capable of explaining its occurrence and abundance in Sicily, for a better management of these populations. We assessed the species habitat preferences by setting 25 large and 25 small nestboxes in five sample areas along an altitudinal gradient of the Madonie Range, and recorded habitat variables, food availability, and demographic data for two years. To obtain synthetic descriptors of the dormice habitat requir…