Marginal increment analysis: a new statistical approach of testing for temporal periodicity in fish age verification
Marginal increment analysis: a new statistical approach of testing for temporal periodicity in fish age verification
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边际增量分析：鱼龄验证中时间周期性测试的新统计方法
DOI：
10.1111/jfb.12062
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发表时间：
2013
影响因子：
2
通讯作者：
Momoko Inchinokawa
中科院分区：
文献类型：
--
作者：
Hiroshi Okamura;Andre E. Punt;Yasuko Semba;Momoko Inchinokawa
本文提出了一种新的、灵活的边际增量分析统计方法，该方法利用具有随机效应的循环-线性回归模型直接考虑循环数据的周期性。将该方法应用于阿拉斯加滑冰Bathyraja parmifera脊椎边缘增量数据。用AIC选择的最佳拟合模型表明，每年都会形成增长带。在已知数据潜在特征的情况下，模拟表明，当不确定度不是很高时，该方法执行得令人满意。
This paper proposes a new and flexible statistical method for marginal increment analysis that directly accounts for periodicity in circular data using a circular–linear regression model with random effects. The method is applied to vertebral marginal increment data for Alaska skateBathyraja parmifera. The best fit model selected using the AIC indicates that growth bands are formed annually. Simulation, where the underlying characteristics of the data are known, shows that the method performs satisfactorily when uncertainty is not extremely high.