构建一个地理加权的非参数回归模型适合测试的测试
Lilis Laome1,2, I Nyoman Budiantara1, Vita Ratnasari1
1Institut Teknologi Sepuluh Nopember, Surabaya 60111 Indonesia.
MethodsX
|January 26, 2024
概括
地理加权非参数回归 (GWNR) 模型比传统模型更好地适应. 一个新的假设测试证实了GWNR.
科学领域:
- 空间统计的空间统计.
- 地理分析 地理分析
- 计量经济学 计量经济学
背景情况:
- 地理加权回归 (GWR) 模型被广泛用于空间分析.
- 地理加权非参数回归 (GWNR) 提供了一个更灵活的方法,具有额外的参数.
- 需要严格测试GWNR模型与其他替代方案的适合性.
研究的目的:
- 开发一种新的假设测试来评估GWNR模型的合适性.
- 用现实数据比较GWNR与混合非参数回归模型的性能.
主要方法:
- 开发一种新的GWNR模型,将混合估计器分线截断和福里埃数列用于未知回归函数.
- 应用合适性测试来评估模型的适用性.
- 使用关于贫困和婴儿死亡率的数据集进行实证分析.
主要成果:
- 与混合非参数回归模型相比,GWNR模型显示出更高的适用性.
- 开发的适合性测试有效评估了模型性能.
- 该研究证实了GWNR模型在社会经济分析中的实际适用性.
结论:
- 拟议的假设测试为验证GWNR模型提供了可靠的方法.
- 对于复杂的空间数据,GWNR比传统的回归技术具有显著的优势.
- 这些发现支持使用GWNR来分析贫困和婴儿死亡率等社会经济指标.
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