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首页> 外文期刊>Australian & New Zealand journal of statistics >SENSITIVITY ANALYSIS OF THE STOCHASTIC GROWTH RATE: THREE EXTENSIONS
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SENSITIVITY ANALYSIS OF THE STOCHASTIC GROWTH RATE: THREE EXTENSIONS

机译：随机增长率的敏感性分析：三种扩展

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The perturbation analysis of population growth rate plays an important role in population biology. The sensitivity and/or elasticity (proportional sensitivity) of population growth rate to changes in the vital rates are regularly used (ⅰ) to predict the effects of environmental perturbations, (ⅱ) to characterize selection gradients on life-history traits, (ⅲ) to evaluate management tactics, (ⅳ) to analyse life table response experiments, and (ⅴ) to calculate the sampling variance in population growth rate. In a stochastic environment, population growth is described by the stochastic growth rate, which gives, with probability 1, the asymptotic time-averaged growth rate of any realization. Tuljapurkar derived the sensitivity and elasticity of the stochastic growth rate to changes in the entries of the stochastic matrices. This paper extends his result to cover three cases, each of which has arisen recently in applications. The first gives the response of the stochastic growth rate to environment-specific perturbations, applied only in a specified subset of the possible environments. The second gives the sensitivity and elasticity of the stochastic growth rate to changes in lower-level parameters. The third applies to stochastic seasonal models, in which the projection matrix for each year is a periodic product of matrices describing seasonal transitions. In this case interest focuses on the sensitivity of the stochastic growth rate to changes in the entries of the seasonal matrices, not entries in the annual matrices. The paper describes examples of problems where each of these extensions is needed, and the algorithms for each of the new calculations.
机译：人口增长率的扰动分析在人口生物学中起着重要的作用。经常使用人口增长率对生命率变化的敏感性和/或弹性（比例敏感性）（ⅰ）预测环境扰动的影响，（ⅱ）表征选择梯度对生活史特征的影响（ⅲ）评估管理策略，（ⅳ）分析寿命表响应实验，（ⅴ）计算人口增长率的抽样方差。在随机环境中，人口增长由随机增长率描述，该增长率以概率1给出任何实现的渐近时间平均增长率。 Tuljapurkar推导了随机增长率对随机矩阵项变化的敏感性和弹性。本文将他的结果扩展到涵盖三种情况，每种情况最近都在应用程序中出现。第一个给出了随机增长率对特定于环境的扰动的响应，仅适用于可能环境的指定子集。第二个参数给出了随机增长率对较低级参数变化的敏感性和弹性。第三个适用于随机季节模型，其中，每年的投影矩阵是描述季节转换的矩阵的周期积。在这种情况下，兴趣集中在随机增长率对季节矩阵条目而不是年度矩阵条目变化的敏感性。本文介绍了每个扩展都需要解决的问题示例，以及每个新计算的算法。

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