Search results for "LINEAR-MODELS"

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Extended differential geometric LARS for high-dimensional GLMs with general dispersion parameter

2018

A large class of modeling and prediction problems involves outcomes that belong to an exponential family distribution. Generalized linear models (GLMs) are a standard way of dealing with such situations. Even in high-dimensional feature spaces GLMs can be extended to deal with such situations. Penalized inference approaches, such as the $$\ell _1$$ or SCAD, or extensions of least angle regression, such as dgLARS, have been proposed to deal with GLMs with high-dimensional feature spaces. Although the theory underlying these methods is in principle generic, the implementation has remained restricted to dispersion-free models, such as the Poisson and logistic regression models. The aim of this…

Statistics and ProbabilityGeneralized linear modelMathematical optimizationGeneralized linear modelsPredictor-€“corrector algorithmGeneralized linear model02 engineering and technologyPoisson distributionDANTZIG SELECTOR01 natural sciencesCross-validationHigh-dimensional inferenceTheoretical Computer Science010104 statistics & probabilitysymbols.namesakeExponential familyLEAST ANGLE REGRESSION0202 electrical engineering electronic engineering information engineeringApplied mathematicsStatistics::Methodology0101 mathematicsCROSS-VALIDATIONMathematicsLeast-angle regressionLinear model020206 networking & telecommunicationsProbability and statisticsVARIABLE SELECTIONEfficient estimatorPredictor-corrector algorithmComputational Theory and MathematicsDispersion paremeterLINEAR-MODELSsymbolsSHRINKAGEStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaStatistics and Computing
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The role of landscape, topography, and geodiversity in explaining vascular plant species richness in a fragmented landscape

2016

We explained vascular plant species richness patterns in a 286 km(2) fragmented landscape with a notable human influence. The objective of this study was two-fold: to test the relative importance of landscape, topography and geodiversity measures, and to compare three different landscape-type variables in species richness modeling. Moreover, we tested if results differ when only native species are considered. We used generalized linear modeling based variation partitioning and generalized additive models with different explanatory variable sets. Landscape and topography explained the majority of the variation but the relative importance of topography and geodiversity was higher in explainin…

NORTHERN FINLANDLAND-COVER DATAspecies diversityspecies richness modelingDIVERSITYGENERALIZED LINEAR-MODELSENVIRONMENTAL HETEROGENEITYCLASSIFICATIONgeodiversiteettitopografiaputkilokasvitPATTERNSDISTRIBUTIONSBIODIVERSITYfragmented landscapeSCALE1172 Environmental sciences
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