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Model Selection Approach (model + selection_approach)
Selected AbstractsGeographic body size gradients in tropical regions: water deficit and anuran body size in the Brazilian CerradoECOGRAPHY, Issue 4 2009Miguel Á. Olalla-Tárraga A recent interspecific study found Bergmann's size clines for Holarctic anurans and proposed an explanation based on heat balance to account for the pattern. However, this analysis was limited to cold temperate regions, and exploring the patterns in warmer tropical climates may reveal other factors that also influence anuran body size variation. We address this using a Cerrado anuran database. We examine the relationship between mean body size in a grid of 1° cells and environmental predictors and test the relative support for four hypotheses using an AIC-based model selection approach. Also, we considered three different amphibian phylogenies to partition the phylogenetic and specific components of the interspecific variation in body size using a method analogous to phylogenetic eigen vector regression (PVR). To consider the potential effects of spatial autocorrelation we use eigenvector-based spatial filters. We found the largest species inhabiting high water deficit areas in the northeast and the smallest in the wet southwest. Our results are consistent with the water availability hypothesis which, coupled with previous findings, suggests that the major determinant of interspecific body size variation in anurans switches from energy to water towards the equator. We propose that anuran body size gradients reflect effects of reduced surface to volume ratios in larger species to control both heat and water balance. [source] Habitat-mediated size selection in endangered Atlantic salmon fry: selectional restoration assessmentEVOLUTIONARY APPLICATIONS (ELECTRONIC), Issue 4 2010Michael M. Bailey Abstract Preservation of adaptive variation is a top priority of many species restoration programs, but most restoration activities are conducted without direct knowledge of selection that might foster or impair adaptation and restoration goals. In this study, we quantified geographic variation in selection on fry size of endangered Atlantic salmon (Salmo salar) during the 6-week period immediately following stocking in the wild. We also used a model selection approach to assess whether habitat variables influence patterns of such selection. We found evidence for significant size-selection in five out of six selection trials. Interestingly, the strength and pattern of selection varied extensively among sites, and model selection suggested that this variation in phenotypic selection was related to geographic variation in the presence of large woody debris and the slope of the stream gradient. The strong selection differentials we observed should be a concern for endangered salmon restoration, whether they reflect natural processes and an opportunity to maintain adaptation, or an indicator of the potentially deleterious phenotypic consequences of hatchery practices. [source] Choosing among competing econometric forecasts: Regression-based forecast combination using model selectionJOURNAL OF FORECASTING, Issue 6 2001Norman R. Swanson Abstract Forecast combination based on a model selection approach is discussed and evaluated. In addition, a combination approach based on ex ante predictive ability is outlined. The model selection approach which we examine is based on the use of Schwarz (SIC) or the Akaike (AIC) Information Criteria. Monte Carlo experiments based on combination forecasts constructed using possibly (misspecified) models suggest that the SIC offers a potentially useful combination approach, and that further investigation is warranted. For example, combination forecasts from a simple averaging approach MSE-dominate SIC combination forecasts less than 25% of the time in most cases, while other ,standard' combination approaches fare even worse. Alternative combination approaches are also compared by conducting forecasting experiments using nine US macroeconomic variables. In particular, artificial neural networks (ANN), linear models, and professional forecasts are used to form real-time forecasts of the variables, and it is shown via a series of experiments that SIC, t -statistic, and averaging combination approaches dominate various other combination approaches. An additional finding is that while ANN models may not MSE-dominate simpler linear models, combinations of forecasts from these two models outperform either individual forecast, for a subset of the economic variables examined. Copyright © 2001 John Wiley & Sons, Ltd. [source] A model selection approach for the identification of quantitative trait loci in experimental crossesJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 4 2002Karl W. Broman Summary. We consider the problem of identifying the genetic loci (called quantitative trait loci (QTLs)) contributing to variation in a quantitative trait, with data on an experimental cross. A large number of different statistical approaches to this problem have been described; most make use of multiple tests of hypotheses, and many consider models allowing only a single QTL. We feel that the problem is best viewed as one of model selection. We discuss the use of model selection ideas to identify QTLs in experimental crosses. We focus on a back-cross experiment, with strictly additive QTLs, and concentrate on identifying QTLs, considering the estimation of their effects and precise locations of secondary importance. We present the results of a simulation study to compare the performances of the more prominent methods. [source] Predictability and model selection in the context of ARCH modelsAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 1 2005Stavros Degiannakis Abstract Most of the methods used in the ARCH literature for selecting the appropriate model are based on evaluating the ability of the models to describe the data. An alternative model selection approach is examined based on the evaluation of the predictability of the models in terms of standardized prediction errors. Copyright © 2005 John Wiley & Sons, Ltd. [source] Body size and extinction risk in Australian mammals: An information-theoretic approachAUSTRAL ECOLOGY, Issue 6 2010RYAN A. CHISHOLM Abstract The critical weight range (CWR) hypothesis for Australian mammals states that extinctions and declines have been concentrated in species with body mass between 35 g and 5.5 kg. The biological basis for this hypothesis is that species of intermediate size are disproportionately impacted by introduced predators. The CWR hypothesis has received support from several statistical studies over the past decade, although the evidence is weaker or non-existent for certain groups such as mesic-zone mammals and arboreal mammals. In this study, we employ an information-theoretic model selection approach to gain further insights into the relationship between body mass and extinction risk in Australian mammals. We find evidence, consistent with the CWR hypothesis, that extinction risk peaks at intermediate body masses for marsupials, rodents and ground-dwelling species, but not for arboreal species. In contrast to previous studies, we find that the CWR describes extinction patterns in the mesic zone as well as the arid zone. In the mesic zone, there is also a weaker tendency for large species above the CWR to be more vulnerable, consistent with extinction patterns on other continents. We find that a more biological plausible Gaussian distribution consistently fits the data better than the polynomial models that have been used in previous studies. Our results justify conservation programmes targeted at species within the CWR across Australia. [source] | |||||||||||||