论文标题
截短的估计值，可变化的功能线性模型
Truncated estimation for varying-coefficient functional linear model
论文作者
论文摘要
可变的功能线性模型考虑响应与预测因子之间的关系，其中响应不仅取决于预测因子，还取决于外源变量。然后，它解释了预测因子的关系，并且响应与外源变量不同。我们考虑了不同模型的截断估计方法。所提出的方法可以通过研究系数函数来阐明功能预测变量与外源变量的任何值的响应有关的时间点。为了获得截短的模型，我们将惩罚性的惩罚性方法应用于引起惩罚。进行了模拟研究以研究所提出的方法的有效性。我们还报告了所提出的方法在分析作物产量数据中的应用，以调查环境因素何时在任何季节与作物产量有关。
Varying-coefficient functional linear models consider the relationship between a response and a predictor, where the response depends not only the predictor but also an exogenous variable. It then accounts for the relation of the predictors and the response varying with the exogenous variable. We consider the method for truncated estimation for varying-coefficient models. The proposed method can clarify to what time point the functional predictor relates to the response at any value of the exogenous variable by investigating the coefficient function. To obtain the truncated model, we apply the penalized likelihood method with the sparsity inducing penalty. Simulation studies are conducted to investigate the effectiveness of the proposed method. We also report the application of the proposed method to the analysis of crop yield data to investigate when an environmental factor relates to the crop yield at any season.
