Distributed Lag Linear and Non-Linear Models in R: The Package dlnm
Distributed Lag Linear and Non-Linear Models in R: The Package dlnm
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DOI：
10.18637/jss.v043.i08
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发表时间：
2011-07-01
影响因子：
5.8
通讯作者：
Gasparrini, Antonio
中科院分区：
文献类型：
--
作者：
Gasparrini, Antonio
分布式滞后非线性模型（DLNM）代表了一个建模框架，可以灵活地描述时间序列数据中显示潜在非线性和延迟效应的关联。这种方法依赖于crossbasis的定义，crossbasis是由两组基函数的组合表示的二维函数空间，这两组基函数分别指定预测器和滞后的维度中的关系。该框架在R软件包dlnm中实现，该软件包提供了执行DLNM系列中各种模型的功能，然后帮助解释结果，重点是图形表示。本文提供了一个概述的功能包，描述的概念和实际步骤，以指定和解释DLNM与应用程序的一个例子，以真实的数据。
Distributed lag non-linear models (DLNMs) represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data. This methodology rests on the definition of a crossbasis, a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm, which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper offers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.