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利用似然性来检验自然界中的 Lévy 飞行搜索模式和一般幂律分布。

Using likelihood to test for Lévy flight search patterns and for general power-law distributions in nature.

作者信息

Edwards Andrew M

机构信息

Pacific Biological Station, Fisheries and Oceans Canada, British Columbia, Canada.

出版信息

J Anim Ecol. 2008 Nov;77(6):1212-22. doi: 10.1111/j.1365-2656.2008.01428.x. Epub 2008 Jul 9.

Abstract
  1. Ecologists are obtaining ever-increasing amounts of data concerning animal movement. A movement strategy that has been concluded for a broad variety of animals is that of Lévy flights, which are random walks whose step lengths come from probability distributions with heavy power-law tails. 2. The exponent that parameterizes the power-law tail, denoted micro, has repeatedly been found to be within the Lévy range of 1 < micro <or= 3. Here, we use Monte Carlo simulations to show that the methods used to infer the value of micro are inaccurate. 3. The widely used method of simply logarithmically transforming a standard histogram of movement lengths has been shown elsewhere to be problematic. Here, we further demonstrate how poor it is, and show that it actually biases estimates of micro towards the Lévy range of 1 < micro <or= 3, and can bias estimates towards the value of micro = 2. Thus, previous reports of animals undergoing Lévy flights, or of micro being close to the reported optimal value of micro = 2, may simply be a consequence of the bias generated by this method. 4. A technique that has been recently recommended is to logarithmically bin the data and then normalize the resulting histogram. We show that this technique also produces biased results, and suffers from similar problems as those just outlined, although to a lesser extent. 5. The proposed solution is to use likelihood. We find that calculating the maximum likelihood estimate of micro gives the most accurate results (having also tested the rank/frequency method). Likelihood has the further advantages of being the easiest method to implement, and of yielding accurate confidence intervals. Results are applicable to power-law distributions in general, and so are not restricted to inference of Lévy flights. 6. We also re-analyse a data set of grey seal movements that was originally reported to demonstrate Lévy flight behaviour. Using Akaike weights, we test four models, and find no evidence for Lévy flights. Overall, our results suggest that Lévy flights might not be as common as previously thought.
摘要
  1. 生态学家们正在获取越来越多关于动物运动的数据。对于各种各样的动物而言,已经得出的一种运动策略是莱维飞行,它是一种随机行走,其步长来自具有重幂律尾的概率分布。2. 用于参数化幂律尾的指数,记为μ,多次被发现处于1<μ≤3的莱维范围内。在此,我们使用蒙特卡罗模拟来表明用于推断μ值的方法是不准确的。3. 广泛使用的简单地对运动长度的标准直方图进行对数变换的方法,在其他地方已被证明是有问题的。在此,我们进一步证明其有多糟糕,并表明它实际上会使μ的估计值偏向1<μ≤3的莱维范围,并且可能使估计值偏向μ = 2的值。因此,先前关于动物进行莱维飞行或μ接近所报道的最优值μ = 2的报告,可能仅仅是这种方法产生的偏差的结果。4. 最近推荐的一种技术是对数据进行对数分箱,然后对所得直方图进行归一化。我们表明这种技术也会产生有偏差的结果,并且存在与上述类似的问题,尽管程度较小。5. 提出的解决方案是使用似然法。我们发现计算μ的最大似然估计给出了最准确的结果(也测试了秩/频率法)。似然法还有易于实施以及能产生准确置信区间的进一步优点。结果一般适用于幂律分布,因此不限于莱维飞行的推断。6. 我们还重新分析了一个最初被报道以证明莱维飞行行为的灰海豹运动数据集。使用赤池权重,我们测试了四个模型,未发现莱维飞行的证据。总体而言,我们的结果表明莱维飞行可能不像以前认为的那么常见。

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