135 resultados para Empirical Bayes Methods


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There has been little study of economic and general attitudes towards the conservation of the Asian elephant. This paper reports and analyses results from surveys conducted in Sri Lanka of attitudes of urban dwellers and farmers towards nature conservation in general and the elephant conservation in particular. The analyses are based on urban and a rural sample. Contingent valuation techniques are used as survey instruments. Multivariate logit regression analysis is used to analyze the respondents’ attitudes towards conservation of elephants. It is found that, although some variations occurred between the samples, the majority of the respondents (both rural and urban) have positive attitudes towards nature conservation in general. However, marked differences in attitudes toward elephant conservation are evident between these two samples: the majority of urban respondents were in favour of elephant conservation; rural respondents expressed a mixture of positive and negative attitudes. Overall, considerable unrecorded and as yet unutilised economic support for conservation of wild elephants exists in Sri Lanka.

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This paper explores the feasibility of adopting an integrated economic approach to raise farmers’ tolerance of the presence of elephants on their farming lands. Responses to this approach were sought from a sample of farmers in the areas affected by human elephant conflict in the northwestern province of Sri Lanka. Results from a contingent valuation survey of their willingness to pay for a scheme to conserve elephants are also reported. Two separate logit regression analyses were undertaken to examine the factors that influence the farmers’ responses for the payment principle question and their opinions on the integrated economic approach. Although found that the majority of the respondents expressed their willingness to pay for the proposed scheme and supported for the implementation of the integrated approach, we have insufficient data yet to determine if their support and financial contribution would be sufficient to set up this programme and also to predict its economic viability. Nevertheless, the overall finding of this study provides an improved economic assessment of the farmers’ attitudes towards the wild elephant in Sri Lanka. At the same time the study shows that, contrary to commonly held assumptions, farmers in this developing country, do support wildlife conservation.

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After introducing the importance of the topic, we examine the economic impacts of wildlife tourism on income and employment as an indicator of the importance of this form of tourism. While such indicators can be important politically and to particular interest groups, they are shown to be an inadequate guide to the economic use and conservation of resources, including wildlife used in tourism. One reason for this (amongst others) is that total economic value must be taken into account in determining economic resource use and this is shown to be quite important in the case of wildlife species. Empirical procedures, such as use of the travel cost method and stated preference methods (for example, contingent valuation) are outlined and the way in which they can be used for determining the optimal economic allocation of land and other resources for wildlife tourism is explained. Economic implications and limitations of some empirical estimates of the importance of wildlife tourism are discussed. This leads on to a consideration of the purpose and usefulness of using economic instruments to manage wildlife tourism.

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OBJECTIVES: 1. To critically evaluate a variety of mathematical methods of calculating effective population size (Ne) by conducting comprehensive computer simulations and by analysis of empirical data collected from the Moreton Bay population of tiger prawns. 2. To lay the groundwork for the application of the technology in the NPF. 3. To produce software for the calculation of Ne, and to make it widely available.

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Global biodiversity loss and its consequences for human welfare and sustainable development have become major concerns. Economists have, therefore, given increasing attention to the policy issues involved in the management of genetic resources. To do so, they often apply empirical methods developed in behavioral and experimental economics to estimate economic values placed on genetic resources. This trend away from almost exclusive dependence on axiomatic methods is welcomed. However, major valuation methods used in behavioral economics raise new scientific challenges. Possibly the most important of these include deficiencies in the knowledge of the public (and researchers) about genetic resources, implications for the formation of values of supplying information to focal individuals, and limits to rationality. These issues are explored for stated-preference techniques of valuation (e.g., contingent valuation) as well as revealed preference techniques, especially the travel cost method. They are illustrated by Australian and Asian examples. Taking into account behavioral and psychological models and empirical evidence, particular attention is given to how elicitation of preferences, and supply of information to individuals, influences their preferences about biodiversity. Policy consequences are outlined.

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In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

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We establish existence of solutions for a finite difference approximation to y = f(x, y, y ') on [0, 1], subject to nonlinear two-point Sturm-Liouville boundary conditions of the form g(i)(y(i),y ' (i)) = 0, i = 0, 1, assuming S satisfies one-sided growth bounds with respect to y '. (C) 2001 Elsevier Science Ltd. All rights reserved.

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An important feature of some conceptual modelling grammars is the features they provide to allow database designers to show real-world things may or may not possess a particular attribute or relationship. In the entity-relationship model, for example, the fact that a thing may not possess an attribute can be represented by using a special symbol to indicate that the attribute is optional. Similarly, the fact that a thing may or may not be involved in a relationship can be represented by showing the minimum cardinality of the relationship as zero. Whether these practices should be followed, however, is a contentious issue. An alternative approach is to eliminate optional attributes and relationships from conceptual schema diagrams by using subtypes that have only mandatory attributes and relationships. In this paper, we first present a theory that led us to predict that optional attributes and relationships should be used in conceptual schema diagrams only when users of the diagrams require a surface-level understanding of the domain being represented by the diagrams. When users require a deep-level understanding, however, optional attributes and relationships should not be used because they undermine users' abilities to grasp important domain semantics. We describe three experiments which we then undertook to test our predictions. The results of the experiments support our predictions.

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In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.

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Learning organizations are a special form of organization where enhancing learning is a strategy to increase intellectual capital. Developing learning organizations has become an imperative for many managers, since an organization's learning methods and rate may be the only source of sustainable competitive advantage. However, learning organization theory tends to be prescriptive and rhetorical, with empirical research still relatively new. This paper contributes to the literature by reporting case-study research in progress based on four Australian organizations. In the organizations studied, use of the learning organization metaphor was coupled with an emergent metaphor: organization as `family". By employing structure mapping of metaphor within analytical induction, both established methods but not combined before, this paper shows how theory might be developed from metaphor.

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This paper examines a range of theoretical issues and the empirical evidence relating to clinical supervision in four mental health professions, namely clinical psychology, occupational therapy, social work, and speech pathology. Despite the widespread acceptance of the value of supervision among practitioners and the large quantity of literature on the topic, there is very little empirical evidence in this area. It is not clear whether supervision actually produces a change in clinician behaviour, nor whether it produces benefits in terms of client outcomes. To date, there is insufficient evidence to demonstrate which styles of supervision are most beneficial for particular types of staff, in terms of their level of experience or learning style. The data suggest that directive forms of supervision, rather than unstructured approaches, are preferred by relatively inexperienced practitioners, and that experienced clinicians also value direct supervision methods when learning new skills or dealing with complex or crisis situations. The available evidence suggests that supervisors typically receive little training in supervision methods. However, to date, we have little information to guide us as to the most effective ways of training supervisors. While acknowledging the urgent need for research, the paper concludes that supervision is likely to form a valuable component of professional development for mental health professionals.