Abstract
With pricing weather derivatives, it is important to investigate the structures of the mean and variance of the temperature processes. However, complicated features of variation in temperature cannot be modeled in terms of a parametric statistical model. This paper investigates the features of temperature processes in Japan using nonparametric regression. Seasonal-trend decomposition using generalized additive models shows the structure of the mean and the variance clearly. In par-ticular, it is proved that seasonal periodicities in the variance vary among areas due to their different climatic characters.
