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Title: Functional regression modeling for agricultural data Authors:  Hidetoshi Matsui - Shiga University (Japan) [presenting]
Keiichi Mochida - RIKEN (Japan)
Abstract: In crop cultivation, it is considered that there are strong relations between information on crop yields and the habitat environment such as temperature and sunlight. In particular, many data sets for the environments are measured over time, and it is desirable to properly handle this information. We report a method for constructing a statistical model that represents the relationship between the data for habitat environment and the crop yield. Time course observations for environments are treated as functional data, and then a functional regression model is considered. We investigate the effect of the environments on the crop yield from the estimated model.