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Bayesian inference and decision theory - A framework for decision making in natural resource management

机译:贝叶斯推理与决策理论-自然资源管理中的决策框架

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摘要

Bayesian inference and decision theory may be used in the solution of relatively complex problems of natural resource management, owing to recent advances in statistical theory and computing. In particular, Markov chain Monte Carlo algorithms provide a computational framework for fitting models of adequate complexity and for evaluating the expected consequences of alternative management actions. We illustrate these features using an example based on management of waterfowl habitat. [References: 26]
机译:由于统计理论和计算的最新进展,贝叶斯推理和决策理论可用于解决相对复杂的自然资源管理问题。尤其是,马尔可夫链蒙特卡罗算法提供了一个计算框架,用于拟合足够复杂的模型并评估替代管理措施的预期结果。我们使用基于水禽栖息地管理的示例来说明这些功能。 [参考:26]

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