995 resultados para SIMULTANEOUS SELECTION


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Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

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Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.

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We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice.

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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

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Consider a general regression model with an arbitrary and unknown link function and a stochastic selection variable that determines whether the outcome variable is observable or missing. The paper proposes U-statistics that are based on kernel functions as estimators for the directions of the parameter vectors in the link function and the selection equation, and shows that these estimators are consistent and asymptotically normal.

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Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.

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In this paper, we explore the conjoint evolution of dispersal and social behaviour. The model investigated is of a population distributed over a number of sites each with a carrying capacity of two adults and an episode of dispersal in the juvenile stage. The fertilities are governed by whether an individual and its neighbour are selfish or co-operative. It is shown that the best dispersal strategy for the co-operative genotype always involves lower levels of dispersal; and further that ecological conditions favouring low levels of dispersal increase the selective advantage of a co-operative genotype. Given this positive feedback, we suggest that in any taxon viscosity and co-operativity will tend to be correlated and bimodally distributed. Hence we predict the existence of two kinds of animal societies; viscous and co-operative (e.g. quasi-social wasps such as Mischocyttarus), and non-viscous and selfish (e.g. communal sphecid wasps such as Cerceris), and relatively few social groups with intermediate levels of co-operativity and viscosity. We also suggest that when one of the two sexes disperses, it will be the sex with lower potential for co-operative behaviour.

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n this paper we study the genericity of simultaneous stabilizability, simultaneous strong stabilizability, and simultaneous pole assignability, in linear multivariable systems. The main results of the paper had been previously established by Ghosh and Byrnes using state-space methods. In contrast, the proofs in the present paper are based on input-output arguments, and are much simpler to follow, especially in the case of simultaneous and simultaneous strong stabilizability. Moreover, the input-output methods used here suggest computationally reliable algorithms for solving these two types of problems. In addition to the main results, we also prove some lemmas on generic greatest common divisors which are of independent interest.

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From the findings of McPhee et al. (1988), there is an expectation that selection in the growing pig for bodyweight gain measured on restricted feeding will result in favourable responses in the rate and efficiency of growth of lean pork on different levels of feeding. This paper examines this in two lines of Australian Large White pigs which have undergone 3 years of selection for high and for low growth rate over a 6-week period starting at 50 kg liveweight. Over this test period, pigs of both lines are all fed the same total amount of grower food, restricted to an estimated 80% of average ad libitum intake. 'Animal production for a consuming world': proceedings of 9th Congress of the AAAAP Societies and 23rd Biennial Conference of the ASAP and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, (DRF). Sydney, Australia.

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Objective To attenuate two strains of Eimeria tenella by selecting for precocious development and evaluate the strains in characterisation trials and by field evaluation, to choose one precocious line for incorporation into an Australian live coccidiosis vaccine for poultry. Design Two strains from non-commercial flocks were passaged through chickens while selecting for precocious development. Each strain was characterised for drug sensitivity, pathogenicity, protection against homologous and heterologous challenge, and oocyst output in replicated experiments in which the experimental unit was a cage of three birds. Oocyst output and/or body weight gain data collected over a 10 to 12 day period following final inoculation were measured. Feed conversion ratios were also calculated where possible. Results Fifteen passages resulted in prepatent periods reduced by 24 h for the Redlands strain (from 144 h to 120 h)and 23 h for the Darryl strain (from 139 h to 116 h). Characterisation trials demonstrated that each precocious line was significantly less pathogenic than its parent strain and each effectively induced immunity that protected chickens against challenge with both the parent strain and other virulent field strains. Both lines had oocyst outputs that, although significantly reduced relative to the parent strains, remained sufficiently high for commercial vaccine production, and both showed susceptibility to coccidiostats. Conclusion Two attenuated lines have been produced that exhibit the appropriate characteristics for use in an Australian live coccidiosis vaccine.

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A novel method, designated the holographic spectrum reconstruction (HSR) method, is proposed for achieving simultaneous display of the spectrum and image of an object in a single plane. A study of the scaling behaviour of both the spectrum and the image has been carried out and based on this study, it is demonstrated that a lensless coherent optical processor can be realized.

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Welcome to the latest collection of papers selected from the International Society for Applied Ethology's (ISAE's) annual congress. The ISAE is a multi-faceted scientific society that supports applied research on animals under the influence of humankind. Every year, we aim to invite congress participants who have submitted papers, plenary talks, run workshops, or presented the memorial lecture on theoretical, review or discussion papers of topical interest to contribute to the Special Issue. These papers are peer-reviewed before being published here in Applied Animal Behaviour Science. International Society for Applied Ethology (ISAE) Special Issue 2004.

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Welcome to the latest collection of papers selected from the International Society for Applied Ethology's (ISAE's) annual congress. The ISAE is a multi-faceted scientific society that supports applied research on animals that are managed by humans. Every year, we aim to invite congress participants who have submitted papers, plenary talks, run workshops, or presented the memorial lecture on theoretical, review or discussion papers of topical interest to contribute to the Special Issue. These papers are peer-reviewed before being published here in Applied Animal Behaviour Science. This year, we have a variety of papers to bring to your attention. The David Wood-Gush Memorial lecture, the keynote address of the congress, was given by Shigeru Watanabe on animal cognition and welfare. His paper highlights how animal's sensory capabilities relate to their welfare. On the topic of human–animal bonds, Stine Christiansen and Björn Forkman explore how animal welfare is assessed in a veterinary context, and how those assessments might be improved by ethologists. Yoshie Kakuma and co-authors report on the discussions from a workshop on the welfare of working and companion dogs in five different countries. Based on their plenary lectures, Michael Cockram discusses the factors that affect farmed animals during road transport and how these might contribute in making decisions to restrict journey times, while Clive Phillips and co-author Danica Peck examine how personality influences the behaviour and interactions between zoo-housed tigers and their keepers. We hope you enjoy these papers. Our sincere thanks go to both the authors and referees, without whom these special issues would not be possible. A selection of papers from the 39th International Congress of the International Society for Applied Ethology (ISAE), Tokyo, Japan, August 2005.

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The leader protease (L-pro) and capsid-coding sequences (P1) constitute approximately 3 kb of the foot-and-mouth disease virus (FMDV). We studied the phylogenetic relationship of 46 FMDV serotype A isolates of Indian origin collected during the period 1968-2005 and also eight vaccine strains using the neighbour-joining tree and Bayesian tree methods. The viruses were categorized under three major groups - Asian, Euro-South American and European. The Indian isolates formed a distinct genetic group among the Asian isolates. The Indian isolates were further classified into different genetic subgroups (<5% divergence). Post-1995 isolates were divided into two subgroups while a few isolates which originated in the year 2005 from Andhra Pradesh formed a separate group. These isolates were closely related to the isolates of the 1970s. The FMDV isolates seem to undergo reverse mutation or onvergent evolution wherein sequences identical to the ancestors are present in the isolates in circulation. The eight vaccine strains included in the study were not related to each other and belonged to different genetic groups. Recombination was detected in the L-pro region in one isolate (A IND 20/82) and in the VP1 coding 1D region in another isolate (A RAJ 21/96). Positive selection was identified at aa positions 23 in the L-pro (P<0.05; 0.046*) and at aa 171 in the capsid protein VP1 (P<0.01; 0.003**).

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Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.