Valderrama Mariano J, Ocaña Francisco A, Aguilera Ana M, Ocaña-Peinado Francisco M
Department of Statistics, University of Granada, 18071-Granada, Spain.
Biometrics. 2010 Jun;66(2):578-85. doi: 10.1111/j.1541-0420.2009.01293.x. Epub 2009 Jul 23.
A functional regression model to forecast the cypress pollen concentration during a given time interval, considering the air temperature in a previous interval as the input, is derived by means of a two-step procedure. This estimation is carried out by functional principal component (FPC) analysis and the residual noise is also modeled by FPC regression, taking as the explicative process the pollen concentration during the earlier interval. The prediction performance is then tested on pollen data series recorded in Granada (Spain) over a period of 10 years.
通过两步法推导了一个功能回归模型，该模型以先前时间间隔内的气温作为输入，来预测给定时间间隔内的柏树花粉浓度。这种估计通过功能主成分（FPC）分析来进行，并且残差噪声也通过FPC回归进行建模，将早期时间间隔内的花粉浓度作为解释过程。然后，利用西班牙格拉纳达记录的10年花粉数据系列对预测性能进行了测试。
