lefko3 : Analysing individual history through size‐classified matrix population models
lefko3 : Analysing individual history through size‐classified matrix population models
复制标题
lefko3：通过按大小分类的矩阵群体模型分析个体历史
DOI：
10.1111/2041-210x.13526
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发表时间：
2020
影响因子：
6.6
通讯作者：
Ehrl?n Johan
中科院分区：
文献类型：
--
作者：
Shefferson Richard P.;Kurokawa Shun;Ehrl?n Johan
个体的历史影响着种群的动态。矩阵投影模型（mpm）用于分析种群动态，但其结构不能纳入这些影响。历史mpm （hMPM）的开发是为了纳入这些影响，但它们的复杂性使它们很少被使用。我们开发了packagelefko3，以提供简单，快速的方法来估计和分析hmpm，以及非历史mpm。packagelefko3处理从数据集组织到hmpm的构建和分析的整个工作流程。数据集管理功能重新组织大多数人口统计数据格式，矩阵创建功能估计原始矩阵和基于函数的矩阵。生命速率可以建模为混合或广义线性模型，模型选择协议涉及当前最佳实践。核心内核是二进制的，即使是具有超过10,000行和列的矩阵也可以在不并行化的情况下快速估计。我们还包括进行基本确定性投影分析的函数。Packagelefko3可以在CRAN上获得，它极大地降低了测试个体历史对种群动态影响的难度。我们提供了三个小插曲来展示如何开发和分析hmpm。
The histories of individuals impact the dynamics of their populations. Matrix projection models (MPMs) are used to analyse population dynamics, but are not structured to incorporate these influences. Historical MPMs (hMPM) were developed to incorporate these impacts, but their complexity has left them little used. We developedrpackagelefko3to provide simple, quick methods to estimate and analyse hMPMs, as well as ahistorical MPMs.Packagelefko3handles the entire workflow from dataset organization to the construction and analysis of hMPMs. Dataset management functions reorganize most demographic data formats, and matrix creation functions estimate both raw and function‐based matrices. Vital rates may be modelled as mixed or generalized linear models, with model selection protocols involving current best practices.The core kernels are binaries allowing even matrices with over 10,000 rows and columns to be estimated quickly without parallelization. We also include functions to conduct basic deterministic projection analyses.Packagelefko3, available on CRAN, dramatically reduces the difficulties in testing the impacts of individual history on population dynamics. We provide three vignettes to showcase how hMPMs can be developed and analysed.