内在的球形光滑方法基于广义的贝齐尔曲线和稀疏度诱导惩罚
Kwan-Young Bak1,2, Jae-Kyung Shin3, Ja-Yong Koo3
1School of Mathematics, Statistics and Data Science, Sungshin Women's University, Seoul, Republic of Korea.
Journal of applied statistics
|June 28, 2023
概括
这项研究引入了一种新的惩罚性平滑方法,使用球形贝济耶曲线对2个球的数据进行分析. 该技术通过自适应性来确定曲线的复杂性,确保数据顺利匹配,而不会丢失本地趋势细节.
科学领域:
- 数学 数学 是一个数学.
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 球形数据分析需要专门的光滑技术.
- 现有的方法可能难以以适应地捕捉本地数据趋势.
研究的目的:
- 开发一种对二球数据的内在惩罚性平滑方法.
- 引入使用球形贝济耶曲线和通用德·卡斯特尔算法的规范化方法.
主要方法:
- 使用由一个通用de Casteljau算法衍生的球形贝济耶曲线.
- 实施局部处罚方案以规范速度差异.
- 采用里曼的区块坐标下降算法来进行高效的计算.
- 尽量减少最小平方标准,以度为基础的规律性约束.
主要成果:
- 拟议的方法通过适应性来确定贝济埃曲线的顺序.
- 处罚导致控制点的稀疏性,使数据驱动的复杂性成为可能.
- 在真实和模拟数据上证明有效性.
- 在不牺牲整体流性的情况下,实现了良好的本地数据趋势适应.
结论:
- 被处罚的贝齐尔曲线平滑方法为2球数据提供了有效的方法.
- 该方法的数据适应性增强了其在各种科学领域的适用性.
关键词:
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