平滑样条方差分析模型及其在复杂海量数据集中的应用

Jingyi Zhang, Honghe Jin, Ye Wang, Xiaoxiao Sun, Ping Ma, Wenxuan Zhong
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引用次数: 6

摘要

利用新开发的数据采集技术,可以方便地访问复杂的海量数据集。尽管平滑样条方差分析模型已被证明在各种领域是有用的,但这些数据集对模型的应用提出了挑战。在本章中,我们对平滑样条方差分析模型进行了综述,并强调了在大量数据集中面临的一些挑战和机遇。我们回顾了两种显著降低模型拟合计算成本的方法。一个实际案例研究被用来说明所审查的方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smoothing Spline ANOVA Models and their Applications in Complex and Massive Datasets
Complex and massive datasets can be easily accessed using the newly developed data acquisition technology. In spite of the fact that the smoothing spline ANOVA models have proven to be useful in a variety of fields, these datasets impose the challenges on the applications of the models. In this chapter, we present a selected review of the smoothing spline ANOVA models and highlight some challenges and opportunities in massive datasets. We review two approaches to significantly reduce the computational costs of fitting the model. One real case study is used to illustrate the performance of the reviewed methods.
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