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Linear Models (linear + models)
Kinds of Linear Models Selected AbstractsModelling the species richness distribution for French Aphodiidae (Coleoptera, Scarabaeoidea)ECOGRAPHY, Issue 2 2004Jorge M. Lobo The species richness distribution of the French Aphodiidae was predicted using Generalized Linear Models to relate the number of species to spatial, topographic and climate variables. The entire French territory was studied, divided into 301 0.72×0.36 degree grid squares; the model was developed using 66 grid squares previously identified as well sampled. After eliminating nine outliers, the final model accounted for 74.8% of total deviance with a mean Jackknife predictive error of 10.5%. Three richest areas could be distinguished: the western head (Brittany), southwestern France, and, to a lesser extent, the northeastern region. Sampling effort should now be focused on the western head, where no square was correctly sampled, and on southwestern France, which was recognised as a diversity hotspot, both for Aphodiidae and for Scarabaeidae. The largest fraction of variability (37%) in the number of species was accounted for by the combined effect of the three groups of explanatory variables. After controlling for the effect of significant climate and topographic variables, spatial variables still explain 27% of variation in species richness, suggesting the existence of a spatial pattern in the distribution of species richness (greater diversity in western France) that can not be explained by the environmental variables considered here. We hypothesize that this longitudinal spatial pattern is due to the relevance of a western colonization pathway along the glacial-interglacial cycles, as well as by the barrier effect played by the Alps. [source] Predictive models of habitat preferences for the Eurasian eagle owl Bubo bubo: a multiscale approachECOGRAPHY, Issue 1 2003Jose Antonio Martínez Habitat preference of eagle owls Bubo bubo were examined through comparing habitat composition around 51 occupied cliffs and 36 non-occupied cliffs in Alicante (E Spain). We employed Generalized Linear Models to examine patterns of habitat preference at three different spatial scales: nest site (7 km2), home range (25 km2), and landscape (100 km2). At the nest site scale, occupied cliffs were more rugged, had a greater proportion of forest surface in the surroundings, and were further from the nearest paved road than unoccupied cliffs. Additionally, probability of having an occupied cliff increased when there was another occupied territory in the surroundings. At both the home range scale and the landscape scale, high probabilities of presence of eagle owls were related to high percentages of Mediterranean scrubland around the cliffs, which are the preferred habitat of European rabbits Oryctolagus cuniculus, the main prey of the owls. We suggest a hierarchical process of habitat selection in the eagle owl concerning suitable trophic resources at the broadest scales and adequate sites for breeding and roosting at the smallest scale. However, it should be noted that some structural features such as the proximity of roads were not necessarily avoided by the owls, but their presence were possibly constrained by systematic killing of individuals. Our paper provides new evidence for the requirement of multi-scale approaches to gain insight into both the different limiting factors for the persistence of populations and the role of individual perception of the environment in the evolution of habitat selection. [source] BIOMOD , optimizing predictions of species distributions and projecting potential future shifts under global changeGLOBAL CHANGE BIOLOGY, Issue 10 2003Wilfried ThuillerArticle first published online: 9 OCT 200 Abstract A new computation framework (BIOMOD: BIOdiversity MODelling) is presented, which aims to maximize the predictive accuracy of current species distributions and the reliability of future potential distributions using different types of statistical modelling methods. BIOMOD capitalizes on the different techniques used in static modelling to provide spatial predictions. It computes, for each species and in the same package, the four most widely used modelling techniques in species predictions, namely Generalized Linear Models (GLM), Generalized Additive Models (GAM), Classification and Regression Tree analysis (CART) and Artificial Neural Networks (ANN). BIOMOD was applied to 61 species of trees in Europe using climatic quantities as explanatory variables of current distributions. On average, all the different modelling methods yielded very good agreement between observed and predicted distributions. However, the relative performance of different techniques was idiosyncratic across species, suggesting that the most accurate model varies between species. The results of this evaluation also highlight that slight differences between current predictions from different modelling techniques are exacerbated in future projections. Therefore, it is difficult to assess the reliability of alternative projections without validation techniques or expert opinion. It is concluded that rather than using a single modelling technique to predict the distribution of several species, it would be more reliable to use a framework assessing different models for each species and selecting the most accurate one using both evaluation methods and expert knowledge. [source] Generalized Linear Models for Insurance Data by Piet de Jong, Gillian Z. HellerINTERNATIONAL STATISTICAL REVIEW, Issue 2 2008Norman R. Draper No abstract is available for this article. [source] Generalized Linear Models in Family StudiesJOURNAL OF MARRIAGE AND FAMILY, Issue 4 2005Zheng WU Generalized linear models (GLMs), as defined by J. A. Nelder and R. W. M. Wedderburn (1972), unify a class of regression models for categorical, discrete, and continuous response variables. As an extension of classical linear models, GLMs provide a common body of theory and methodology for some seemingly unrelated models and procedures, such as the logistic, Poisson, and probit models, that are increasingly used in family studies. This article provides an overview of the principle and the key components of GLMs, such as the exponential family of distributions, the linear predictor, and the link function. To illustrate the application of GLMs, this article uses Canadian national survey data to build an example focusing on the number of close friends among older adults. The article concludes with a discussion of the strengths and weaknesses of GLMs. [source] Childhood conditions and education as determinants of adult height and obesity among Greenland InuitAMERICAN JOURNAL OF HUMAN BIOLOGY, Issue 3 2010P. Bjerregaard Height and obesity are risk factors for cardiovascular disease and other physical and mental health conditions. Their association with childhood socioeconomic position has been demonstrated in studies among European and a few third world populations. In a random sample of adult Greenland Inuit (N = 2302) we studied the association between childhood socioeconomic conditions and height as well as prevalence of obesity (BMI , 30) in a cross sectional design. In block recursive graphical independence models, height was associated with mother's place of birth, birth cohort, childhood residence, alcohol problems in childhood home, and education among both men and women. Obesity was associated with mother's place of birth (for men) and with alcohol problems (for women). In General Linear Models, men with an all rural background and no education beyond primary school measured on average 165.1 cm compared with 172.1 cm for men with an all urban background (P < 0.001); women measured 153.9 and 161.1 cm (P < 0.001). Rural-urban differences in prevalence of obesity were not statistically significant. The height differences were considerably larger than between educational groups in European countries and of the same order of magnitude as those reported between men from the 17th century and men from 400 BC in the European and Mediterranean region. The rural-urban gradient in height follows the socioeconomic gradient and may negatively affect cardiovascular risk among the rural Greenlanders, while their physically active lifestyle and high consumption of n-3 fatty acids may counteract this. Am. J. Hum. Biol., 2010. © 2009 Wiley-Liss, Inc. [source] Dynamics of species-rich upland hay meadows over 15 years and their relation with agricultural management practicesAPPLIED VEGETATION SCIENCE, Issue 3 2007C.N.R. Critchley Stace (1997) Abstract Questions: Has the species-rich vegetation of upland hay meadows been maintained under low intensity management imposed by an agri-environment scheme? Is the target plant community re-establishing where it has been modified previously by intensive agricultural practices? What combinations of management practices and soil properties are associated with changes towards or away from the target community? Location: The Pennines, northern England, UK. Methods: A survey of 116 hay meadows in 1987 was repeated in 2002 by recording plant species in permanent quadrats. Changes in community variables (species richness, Ellenberg values, upland hay meadow community coefficients) were analysed in species-rich, modified species-rich and degraded grassland types. Redundancy Analysis and Generalised Linear Models were used to show the relationship between management practices and soil properties and change in species composition and community variables. Results: Few sites contained the species-rich grassland type, and here forb richness declined. In the modified species-rich type, total and grass species richness increased but Ellenberg N-values also increased. Total and grass species richness increased in the degraded type and the community coefficient increased. Management was weakly related to change in species composition but showed clear relationships with the community variables. Re-establishment of the target species-rich community was more likely with late cutting, in the absence of cattle or prolonged spring grazing, and at lower soil nutrient status. Conclusion: The species-rich community was not maintained but some reversion occurred in degraded grassland. Inorganic fertiliser application and intensive spring grazing should be avoided and cutting delayed until late July. [source] Functional Generalized Linear Models with Images as PredictorsBIOMETRICS, Issue 1 2010Philip T. Reiss Summary Functional principal component regression (FPCR) is a promising new method for regressing scalar outcomes on functional predictors. In this article, we present a theoretical justification for the use of principal components in functional regression. FPCR is then extended in two directions: from linear to the generalized linear modeling, and from univariate signal predictors to high-resolution image predictors. We show how to implement the method efficiently by adapting generalized additive model technology to the functional regression context. A technique is proposed for estimating simultaneous confidence bands for the coefficient function; in the neuroimaging setting, this yields a novel means to identify brain regions that are associated with a clinical outcome. A new application of likelihood ratio testing is described for assessing the null hypothesis of a constant coefficient function. The performance of the methodology is illustrated via simulations and real data analyses with positron emission tomography images as predictors. [source] A Primer on Linear Models by MONAHAN, J. F.BIOMETRICS, Issue 3 2009Muni S. Srivastava No abstract is available for this article. [source] Mixture Generalized Linear Models for Multiple Interval Mapping of Quantitative Trait Loci in Experimental CrossesBIOMETRICS, Issue 2 2009Zehua Chen Summary Quantitative trait loci mapping in experimental organisms is of great scientific and economic importance. There has been a rapid advancement in statistical methods for quantitative trait loci mapping. Various methods for normally distributed traits have been well established. Some of them have also been adapted for other types of traits such as binary, count, and categorical traits. In this article, we consider a unified mixture generalized linear model (GLIM) for multiple interval mapping in experimental crosses. The multiple interval mapping approach was proposed by Kao, Zeng, and Teasdale (1999, Genetics152, 1203,1216) for normally distributed traits. However, its application to nonnormally distributed traits has been hindered largely by the lack of an efficient computation algorithm and an appropriate mapping procedure. In this article, an effective expectation,maximization algorithm for the computation of the mixture GLIM and an epistasis-effect-adjusted multiple interval mapping procedure is developed. A real data set, Radiata Pine data, is analyzed and the data structure is used in simulation studies to demonstrate the desirable features of the developed method. [source] An Introduction to Generalized Linear Models, 3rd edition by DOBSON, A. J. and BARNETT, A. G.BIOMETRICS, Issue 2 2009Article first published online: 28 MAY 200 No abstract is available for this article. [source] Bayesian Analysis for Generalized Linear Models with Nonignorably Missing CovariatesBIOMETRICS, Issue 3 2005Lan Huang Summary We propose Bayesian methods for estimating parameters in generalized linear models (GLMs) with nonignorably missing covariate data. We show that when improper uniform priors are used for the regression coefficients, ,, of the multinomial selection model for the missing data mechanism, the resulting joint posterior will always be improper if (i) all missing covariates are discrete and an intercept is included in the selection model for the missing data mechanism, or (ii) at least one of the covariates is continuous and unbounded. This impropriety will result regardless of whether proper or improper priors are specified for the regression parameters, ,, of the GLM or the parameters, ,, of the covariate distribution. To overcome this problem, we propose a novel class of proper priors for the regression coefficients, ,, in the selection model for the missing data mechanism. These priors are robust and computationally attractive in the sense that inferences about , are not sensitive to the choice of the hyperparameters of the prior for , and they facilitate a Gibbs sampling scheme that leads to accelerated convergence. In addition, we extend the model assessment criterion of Chen, Dey, and Ibrahim (2004a, Biometrika91, 45,63), called the weighted L measure, to GLMs and missing data problems as well as extend the deviance information criterion (DIC) of Spiegelhalter et al. (2002, Journal of the Royal Statistical Society B64, 583,639) for assessing whether the missing data mechanism is ignorable or nonignorable. A novel Markov chain Monte Carlo sampling algorithm is also developed for carrying out posterior computation. Several simulations are given to investigate the performance of the proposed Bayesian criteria as well as the sensitivity of the prior specification. Real datasets from a melanoma cancer clinical trial and a liver cancer study are presented to further illustrate the proposed methods. [source] Variable Selection for Marginal Longitudinal Generalized Linear ModelsBIOMETRICS, Issue 2 2005Eva Cantoni Summary Variable selection is an essential part of any statistical analysis and yet has been somewhat neglected in the context of longitudinal data analysis. In this article, we propose a generalized version of Mallows's Cp (GCp) suitable for use with both parametric and nonparametric models. GCp provides an estimate of a measure of model's adequacy for prediction. We examine its performance with popular marginal longitudinal models (fitted using GEE) and contrast results with what is typically done in practice: variable selection based on Wald-type or score-type tests. An application to real data further demonstrates the merits of our approach while at the same time emphasizing some important robust features inherent to GCp. [source] Standard Errors for EM Estimates in Generalized Linear Models with Random EffectsBIOMETRICS, Issue 3 2000Herwig Friedl Summary. A procedure is derived for computing standard errors of EM estimates in generalized linear models with random effects. Quadrature formulas are used to approximate the integrals in the EM algorithm, where two different approaches are pursued, i.e., Gauss-Hermite quadrature in the case of Gaussian random effects and nonparametric maximum likelihood estimation for an unspecified random effect distribution. An approximation of the expected Fisher information matrix is derived from an expansion of the EM estimating equations. This allows for inferential arguments based on EM estimates, as demonstrated by an example and simulations. [source] The community-wide and guild-specific effects of pubescence on the folivorous insects of manzanitas Arctostaphylos spp.ECOLOGICAL ENTOMOLOGY, Issue 4 2003Melissa R. Andres Abstract., 1.,Insect communities on 26 species of manzanita Arctostaphylos spp. (Ericaceae) were sampled in order to examine the effects of variation in foliar pubescence traits on a community of folivorous insects. Manzanitas vary widely in pubescence density, length, and glandularity both within and between species. 2.,Linear models were fitted and evaluated to determine whether pubescence traits are associated with the species richness and abundance of folivorous insects after accounting for the effects of other relevant habitat and host-plant related characteristics. 3.,Pubescence traits were clearly associated with both community-wide and guild-specific variation in the structure of the folivorous insect community of manzanitas, however the effects of pubescence were manifested primarily as effects on the abundance of folivores not on species richness. The species richness of folivorous insects on manzanitas was not associated with pubescence density or length but was associated positively with glandularity. 4.,The abundance of all guilds except leaf-mining insects was lower on manzanitas having longer pubescence. In contrast, the abundance of external-chewing insects was higher on plants having denser pubescence and on plants having glandular pubescence. 5.,Overall, the results suggest that both longer pubescence and the amount of contact between an insect and pubescence act quantitatively to decrease the abundance of external-feeding guilds of folivorous insects. The abundance of species in internal-feeding guilds that oviposit directly on leaves is unrelated to foliar pubescence traits in the host plant. [source] Soil moisture,temperature relationships: results from two field experimentsHYDROLOGICAL PROCESSES, Issue 15 2003Venkat Lakshmi Abstract This paper analyses data from two field experiments in Chickasha, Oklahoma, and Tifton, Georgia, carried out in July 1999 and June 2000 respectively. The observations on soil moisture at two depths, viz. 0,2·5 and 0,5·0 cm, surface temperature, and temperatures at 1, 5 and 10 cm depths are analysed. The relationship between the soil moisture and the temperature variability in time is examined as a function of vegetation type and location. Results from these experiments show that, during drydown, surface temperature shows an increase that corresponds to a decrease in the soil moisture. Linear models for prediction of soil moisture (at both depths) using surface temperature observations are examined. Copyright © 2003 John Wiley & Sons, Ltd. [source] Linear models for minimizing misclassification costs in bankruptcy predictionINTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 3 2001Sudhir Nanda This paper illustrates how a misclassification cost matrix can be incorporated into an evolutionary classification system for bankruptcy prediction. Most classification systems for predicting bankruptcy have attempted to minimize misclassifications. The minimizing misclassification approach assumes that Type I and Type II error costs for misclassifications are equal. There is evidence that these costs are not equal and incorporating costs into the classification systems can lead to better and more desirable results. In this paper, we use the principles of evolution to develop and test a genetic algorithm (GA) based approach that incorporates the asymmetric Type I and Type II error costs. Using simulated and real-life bankruptcy data, we compare the results of our proposed approach with three linear approaches: statistical linear discriminant analysis (LDA), a goal programming approach, and a GA-based classification approach that does not incorporate the asymmetric misclassification costs. Our results indicate that the proposed approach, incorporating Type I and Type II error costs, results in lower misclassification costs when compared to LDA and GA approaches that do not incorporate misclassification costs. Copyright © 2001 John Wiley & Sons, Ltd. [source] Linear models to predict the digestible lipid content of fish dietsAQUACULTURE NUTRITION, Issue 5 2009J. SALES Abstract Values for the digestible contents of nutrients in diets and feed ingredients are of utmost importance in nutritional strategies for fish. Prediction from dietary composition would eliminate lengthy, tedious and demanding digestibility experiments with fish. Apparent digestible lipid (DL) content [range 7.6,353.4 g kg,1 dry matter (DM)] in compound diets can be predicted with high accuracy (n = 610; studies =127; fish species = 34; R2 = 0.9515; RMSE = 16.9504) from dietary crude lipid (CL) content (range 12.0,388.7 g kg,1 DM) by the linear regression equation DL =,2.7303 + 0.9123 CL. Validation of this equation against 65 values from 15 independent studies presented R2 and mean prediction error (MPE) values of 0.9947 and 0.0671, respectively. The corresponding equation for 37 individual feed ingredients evaluated in 24 studies with 18 fish species (n = 180) was found to be DL = ,1.5824 + 0.8654 CL (R2 = 0.9717; RMSE = 8.3765). However, validation of the latter is currently hampered by a lack of independent values. [source] Patch Occupancy and Potential Metapopulation Dynamics of Three Forest Mammals in Fragmented Afromontane Forest in South AfricaCONSERVATION BIOLOGY, Issue 4 2000Michael J. Lawes We recorded patch occupancy of blue duiker ( Philantomba monticola), tree hyrax ( Dendrohyrax arboreus), and samango monkey (Cercopithecus mitis labiatus) in 199 forest patches. Their rarity is ascribed to the fragmentation and destruction of their forest habitat. Incidence functions, derived from presence and absence data, were formulated as generalized linear models, and environmental effects were included in the fitted logistic models. The small and mostly solitary hyrax and duiker persisted in smaller patches than the large and social monkey. Although this result follows expectations based on relative home-range sizes of each species, the incidence probability of the samango monkey was invariant with increasing isolation, whereas a gradual decrease with increasing isolation was observed for the hyrax and duiker. Group dynamics may inhibit dispersal and increase the isolation effect in social species such as samango monkeys. A mainland-island metapopulation model adequately describes patterns of patch occupancy by the hyrax and duiker, but the monkeys' poor dispersal ability and obvious area-dependent extirpation suggest that they exist in transient, nonequilibrium (declining) metapopulations. Through identification of large forest patches for careful protection and management, the survival of all three species,especially the monkey,could be prolonged. Because no functional metapopulation may exist for the monkey, however, this is an emergency measure. For the duiker and hyrax, larger patches should form part of a network of smaller and closer patches in a natural matrix. Resumen: Investigamos la persistencia de tres mamíferos forestales raros de tamaño mediano (2,9 kg) en los bosques fragmentados de cinturón de niebla Podocarpus en la región central de la provincia KwaZulu-Natal, Sudáfrica. Registramos la ocupación del duiker azul ( Philantomba monticola), el hyrax arborícola ( Dendrohyrax arboreus) y el mono samango (Cercopithecus mitis labiatus) en 199 parches forestales. Su rareza se atribuye a la fragmentación y destrucción de su hábitat forestal. Las funciones de incidencia, derivadas de datos de presencia y ausencia, fueron formuladas como modelos lineales generalizados, y los efectos ambientales fueron incluidos en los modelos logísticos ajustados. Los pequeños y mayormente solitarios hyrax y duiker persistieron en parches más pequeños que los monos, que son más grandes y más sociables. A pesar de que este resultado obedece a expectativas basadas en tamaños de rango de hogar relativos de cada especie, la probabilidad de incidencia del mono samango no cambió con un incremento en el aislamiento, mientras que una disminución gradual al crecer el aislamiento se observó en hyrax y duiker. Las dinámicas de grupos podrían inhibir la dispersión e incrementar el efecto de aislamiento en especies sociables como lo es el mono samango. Un modelo de metapoblación continente-isla describe adecuadamente los patrones de la ocupación de parches por hyrax y duiker; sin embargo, la pobre capacidad de dispersión de los monos y la obvia extirpación área-dependente sugiere que estos existen en metapoblaciones transitorias, desequilibradas (en disminución). Mediante la identificación de parches forestales grandes para la protección y manejo cuidadosos, la supervivencia de las tres especies ( pero especialmente la de los monos) podría ser prolongada. Sin embargo, debido a que no existen metapoblaciones funcionales de monos, esta es una medida de emergencia. Para el duiker y el hyrax, los parches grandes deberán formar parte de una red de parches más pequeños y más cercanos en una matriz natural. [source] Neural Network Earnings per Share Forecasting Models: A Comparative Analysis of Alternative MethodsDECISION SCIENCES, Issue 2 2004Wei Zhang ABSTRACT In this paper, we present a comparative analysis of the forecasting accuracy of univariate and multivariate linear models that incorporate fundamental accounting variables (i.e., inventory, accounts receivable, and so on) with the forecast accuracy of neural network models. Unique to this study is the focus of our comparison on the multivariate models to examine whether the neural network models incorporating the fundamental accounting variables can generate more accurate forecasts of future earnings than the models assuming a linear combination of these same variables. We investigate four types of models: univariate-linear, multivariate-linear, univariate-neural network, and multivariate-neural network using a sample of 283 firms spanning 41 industries. This study shows that the application of the neural network approach incorporating fundamental accounting variables results in forecasts that are more accurate than linear forecasting models. The results also reveal limitations of the forecasting capacity of investors in the security market when compared to neural network models. [source] Subjective quality of life aspects predict depressive symptoms over time: results from a three-wave longitudinal studyACTA PSYCHIATRICA SCANDINAVICA, Issue 6 2009C. Kuehner Objective:, Little is known about predictive effects of quality of life aspects on the course of depressive symptoms in clinical and non-clinical settings. This study examines longitudinal associations between depressive symptoms and subjective quality of life (QOL) dimensions using a parallel sample of depressed patients and community controls. Method:, Eighty-two depressed patients were investigated 1, 6, and 42 months after hospital discharge together with 76 community controls regarding depressive symptoms measured by Montgomery Asberg Depression Rating Scale (MADRS) and QOL (WHOQOL-BREF). Data analysis included time-lagged linear models. Results:, Physical, psychological, environmental and overall QOL, controlled for depressive symptoms, predicted future depression levels. Group status did not moderate these associations. Depressive symptoms predicted future QOL levels only regarding social relations. Conclusion:, Our study suggests that subjective QOL domains have prognostic value for the course of depressive symptoms over time, both in patient and community samples. Respective self-perceptions should therefore be directly addressed by therapeutic and preventive interventions. [source] Neophyte species richness at the landscape scale under urban sprawl and climate warmingDIVERSITY AND DISTRIBUTIONS, Issue 6 2009Michael P. Nobis Abstract Aim, Land use and climate are two major components of global environmental change but our understanding of their simultaneous and interactive effects upon biodiversity is still limited. Here, we investigated the relationship between the species richness of neophytes, i.e. non-native vascular plants introduced after 1500 AD, and environmental covariates to draw implications for future dynamics under land-use and climate change. Location, Switzerland, Central Europe. Methods, The distribution of vascular plants was derived from a systematic national grid of 1 km2 quadrates (n = 456; Swiss Biodiversity Monitoring programme) including 1761 species, 122 of which were neophytes. Generalized linear models (GLMs) were used to correlate neophyte species richness with environmental covariates. The impact of land-use and climate change was thereafter evaluated by projections for the years 2020 and 2050 using scenarios of moderate and strong changes for climate warming (IPCC) and urban sprawl (NRP 54). Results, Mean annual temperature and the amount of urban areas explained neophyte species richness best, with a high predictive power of the corresponding model (cross-validated D2 = 0.816). Climate warming had a stronger impact on the potential increase in the mean neophyte species richness (up to 191% increase by 2050) than ongoing urban sprawl (up to 10% increase) independently from variable interactions and model extrapolations to non-analogue environments. Main conclusions, In contrast to other vascular plants, the prediction of neophyte species richness at the landscape scale in Switzerland requires few variables only, and regions of highest species richness of the two groups do not coincide. The neophyte species richness is basically driven by climatic (temperature) conditions, and urban areas additionally modulate small-scale differences upon this coarse-scale pattern. According to the projections climate warming will contribute to the future increase in neophyte species richness much more than ongoing urbanization, but the gain in new neophyte species will be highest in urban regions. [source] Non-iterative equivalent linearization of inelastic SDOF systems for earthquakes in Japan and CaliforniaEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 11 2010Katsuichiro Goda Abstract The seismic performance of existing structures can be assessed based on nonlinear static procedures, such as the Capacity Spectrum Method. This method essentially approximates peak responses of an inelastic single-degree-of-freedom (SDOF) system using peak responses of an equivalent linear SDOF model. In this study, the equivalent linear models of inelastic SDOF systems are developed based on the constant strength approach, which does not require iteration for assessing the seismic performance of existing structures. To investigate the effects of earthquake type and seismic region on the equivalent linear models, four ground-motion data sets,Japanese crustal/interface/inslab records and California crustal records,are compiled and used for nonlinear dynamic analysis. The analysis results indicate that: (1) the optimal equivalent linear model parameters (i.e. equivalent vibration period ratio and damping ratio) decrease with the natural vibration period, whereas they increase with the strength reduction factor; (2) the impacts of earthquake type and seismic region on the equivalent linear model parameters are not significant except for short vibration periods; and (3) the degradation and pinching effects affect the equivalent linear model parameters. We develop prediction equations for the optimal equivalent linear model parameters based on nonlinear least-squares fitting, which improve and extend the current nonlinear static procedure for existing structures with degradation and pinching behavior. Copyright © 2010 John Wiley & Sons, Ltd. [source] Dynamic systems with high damping rubber: Nonlinear behaviour and linear approximationEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 13 2008Andrea Dall'Asta Abstract High damping rubber (HDR) shows a quite complex constitutive behaviour, which is nonlinear with respect to strain and is dependent on the strain rate. In addition, it exhibits a transient response during which the material properties change (scragging or more generally the Mullins effect). A number of recent works were dedicated to analysing and modelling material behaviour. This paper studies the nonlinear dynamics of systems with restoring force produced by HDR-based devices in order to propose a procedure to define equivalent linear models considering both transient and stationary behaviours. The reliability of these linear models is tested by evaluating the upper and lower bounds of the seismic response of a structural system equipped with HDR-based devices (structural system with dissipative bracings and isolated systems). Copyright © 2008 John Wiley & Sons, Ltd. [source] Approximate modal decomposition of inelastic dynamic responses of wall buildingsEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 9 2004C. Sangarayakul Abstract Two approximate methods for decomposing complicated inelastic dynamic responses of wall buildings into simple modal responses are presented. Both methods are based on the equivalent linear concept, where a non-linear structure is represented by a set of equivalent linear models. One linear model is used for representing only one vibration mode of the non-linear structure, and its equivalent linear parameters are identified from the inelastic response time histories by using a numerical optimizer. Several theoretical relations essential for the modal decomposition are derived under the framework of complex modal analysis. Various numerical examinations have been carried out to check the validity of the proposed modal decomposition methods, and the results are quite satisfactory in all cases. Fluctuating bending moment and shear at any location along the wall height contributed by each individual vibration mode can be obtained. Modal contributions to shear and flexural strength demands, as well as the corresponding modal properties, under various seismic loading conditions can also be identified and examined in detail. Furthermore, the effects of higher vibration modes on seismic demands of wall buildings are investigated by using the modal decomposition methods. Several new insights into the complicated inelastic dynamics of multi-story wall buildings are presented. Copyright © 2004 John Wiley & Sons, Ltd. [source] Impact of Scribes on Performance Indicators in the Emergency DepartmentACADEMIC EMERGENCY MEDICINE, Issue 5 2010Rajiv Arya MD Abstract Objectives:, The objective was to quantify the effect of scribes on three measures of emergency physician (EP) productivity in an adult emergency department (ED). Methods:, For this retrospective study, 243 clinical shifts (of either 10 or 12 hours) worked by 13 EPs during an 18-month period were selected for evaluation. Payroll data sheets were examined to determine whether these shifts were covered, uncovered, or partially covered (for less than 4 hours) by a scribe; partially covered shifts were grouped with uncovered shifts for analysis. Covered shifts were compared to uncovered shifts in a clustered design, by physician. Hierarchical linear models were used to study the association between percentage of patients with which a scribe was used during a shift and EP productivity as measured by patients per hour, relative value units (RVUs) per hour, and turnaround time (TAT) to discharge. Results:, RVUs per hour increased by 0.24 units (95% confidence interval [CI] = 0.10 to 0.38, p = 0.0011) for every 10% increment in scribe usage during a shift. The number of patients per hour increased by 0.08 (95% CI = 0.04 to 0.12, p = 0.0024) for every 10% increment of scribe usage during a shift. TAT was not significantly associated with scribe use. These associations did not lose significance after accounting for physician assistant (PA) use. Conclusions:, In this retrospective study, EP use of a scribe was associated with improved overall productivity as measured by patients treated per hour (Pt/hr) and RVU generated per hour by EPs, but not as measured by TAT to discharge. ACADEMIC EMERGENCY MEDICINE 2010; 17:490,494 © 2010 by the Society for Academic Emergency Medicine [source] Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictorsECOGRAPHY, Issue 6 2009Alexandra D. Syphard Prediction maps produced by species distribution models (SDMs) influence decision-making in resource management or designation of land in conservation planning. Many studies have compared the prediction accuracy of different SDM modeling methods, but few have quantified the similarity among prediction maps. There has also been little systematic exploration of how the relative importance of different predictor variables varies among model types and affects map similarity. Our objective was to expand the evaluation of SDM performance for 45 plant species in southern California to better understand how map predictions vary among model types, and to explain what factors may affect spatial correspondence, including the selection and relative importance of different environmental variables. Four types of models were tested. Correlation among maps was highest between generalized linear models (GLMs) and generalized additive models (GAMs) and lowest between classification trees and GAMs or GLMs. Correlation between Random Forests (RFs) and GAMs was the same as between RFs and classification trees. Spatial correspondence among maps was influenced the most by model prediction accuracy (AUC) and species prevalence; map correspondence was highest when accuracy was high and prevalence was intermediate (average prevalence for all species was 0.124). Species functional type and the selection of climate variables also influenced map correspondence. For most (but not all) species, climate variables were more important than terrain or soil in predicting their distributions. Environmental variable selection varied according to modeling method, but the largest differences were between RFs and GLMs or GAMs. Although prediction accuracy was equal for GLMs, GAMs, and RFs, the differences in spatial predictions suggest that it may be important to evaluate the results of more than one model to estimate the range of spatial uncertainty before making planning decisions based on map outputs. This may be particularly important if models have low accuracy or if species prevalence is not intermediate. [source] Effects of species' ecology on the accuracy of distribution modelsECOGRAPHY, Issue 1 2007Jana M. McPherson In the face of accelerating biodiversity loss and limited data, species distribution models , which statistically capture and predict species' occurrences based on environmental correlates , are increasingly used to inform conservation strategies. Additionally, distribution models and their fit provide insights on the broad-scale environmental niche of species. To investigate whether the performance of such models varies with species' ecological characteristics, we examined distribution models for 1329 bird species in southern and eastern Africa. The models were constructed at two spatial resolutions with both logistic and autologistic regression. Satellite-derived environmental indices served as predictors, and model accuracy was assessed with three metrics: sensitivity, specificity and the area under the curve (AUC) of receiver operating characteristics plots. We then determined the relationship between each measure of accuracy and ten ecological species characteristics using generalised linear models. Among the ecological traits tested, species' range size, migratory status, affinity for wetlands and endemism proved most influential on the performance of distribution models. The number of habitat types frequented (habitat tolerance), trophic rank, body mass, preferred habitat structure and association with sub-resolution habitats also showed some effect. In contrast, conservation status made no significant impact. These findings did not differ from one spatial resolution to the next. Our analyses thus provide conservation scientists and resource managers with a rule of thumb that helps distinguish, on the basis of ecological traits, between species whose occurrence is reliably or less reliably predicted by distribution models. Reasonably accurate distribution models should, however, be attainable for most species, because the influence ecological traits bore on model performance was only limited. These results suggest that none of the ecological traits tested provides an obvious correlate for environmental niche breadth or intra-specific niche differentiation. [source] Species richness patterns and metapopulation processes , evidence from epiphyte communities in boreo-nemoral forestsECOGRAPHY, Issue 2 2006Swantje Löbel For several epiphyte species, dispersal limitation and metapopulation dynamics have been suggested. We studied the relative importance of local environmental conditions and spatial aggregation of species richness of facultative and obligate epiphytic bryophytes and lichens within two old-growth forests in eastern Sweden. The effect of the local environment was analyzed using generalized linear models (GLM). We tested whether species richness was spatially structured by fitting variogram models to the residuals of the GLM. In addition, we analyzed the species-area relationship (area=tree diameter). Different environmental variables explained the richness of different species groups (bryophytes vs lichens, specialists vs generalists, sexual vs asexual dispersal). In most groups, the total variation explained by environmental variables was higher than the variation explained by the spatial model. Spatial aggregation was more pronounced in asexually than in sexually dispersed species. Bryophyte species richness was only poorly predicted by area, and lichen species richness was not explained by area at all. Spatial aggregation may indicate effects of dispersal limitation and metapopulation dynamics on community species richness. Our results suggest that species groups differ in habitat requirements and dispersal abilities; there were indications that presence of species with different dispersal strategies is linked to the age of the host tree. Separate analyses of the species richness of species groups that differ in the degree of habitat specialization and dispersal ability give insights into the processes determining community species richness. The poor species-area relationship, especially in lichens, may indicate species turnover rather than accumulation during the lifetime of the host tree. Epiphyte species extinctions may be mainly caused by deterministic processes, e.g. changes in habitat conditions as the host tree grows, ages and dies, rather than by stochastic population processes. [source] On the analysis of non-linear allometriesECOLOGICAL ENTOMOLOGY, Issue 1 2009ROBERT J. KNELL Abstract 1.,Non-linear allometries are those where a log,log scatterplot of trait size against body size deviates from simple linearity. These are found in many insects, including the horns of beetles, the forceps of earwigs, and the heads of certain castes of ant. 2.,Non-linear allometries are often associated with polyphenism that is itself related to behaviour: for example, the alternative mating tactics displayed by many species of beetle are widely associated with dimorphisms in horn size. 3.,This paper critically reviews the current techniques used to analyse these datasets. 4.,Recommendations include the use of scatterplots and assessment of the goodness of fit of simple linear models as an initial screen for non-linear allometry. The use of recently developed algorithms for ,segmented' regression to analyse continuous allometric relationships, and a pragmatic approach to the analysis of discontinuous relationships that recognises that there is no simple way to distinguish between morphs in some cases, and that all of the proposed methods for doing so have some drawbacks. 5.,Worked examples of the analysis of two sets of data from animals that have been the subject of controversy regarding the nature of their allometric relationships are given: further worked examples are provided as online Supporting Information. [source] | |||||||||||||||||||||||||||||||||||||||||||