Shumway R H, Azari A S, Pawitan Y
Division of Statistics, University of California, Davis 95616.
Environ Res. 1988 Apr;45(2):224-41. doi: 10.1016/s0013-9351(88)80049-5.
Linear and nonlinear models are used to investigate possible associations between mortality and pollution and weather effects in Los Angeles County. State-space modeling and time and frequency domain regressions are used to modify the data base and to isolate significant weather factors and pollutants associated with increased daily mortality. Nonparametric and parametric regression methods are used to develop nonlinear dose-response profiles relating mortality to temperature and to the statistically significant pollutants. A parametric nonlinear time series model involving linear and squared terms in temperature and the logarithm of pollution provides a reasonable predictive model.
线性和非线性模型用于研究洛杉矶县死亡率与污染及天气影响之间的可能关联。状态空间建模以及时域和频域回归用于修正数据库，并分离出与每日死亡率增加相关的重要天气因素和污染物。非参数和参数回归方法用于建立将死亡率与温度以及具有统计学意义的污染物相关联的非线性剂量反应曲线。一个涉及温度的线性项和平方项以及污染对数的参数非线性时间序列模型提供了一个合理的预测模型。
