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贝叶斯核密度估计

贝叶斯核密度估计(Bayesian Kernel Density Estimation, BKDE)是一种非参数方法,通过将核平滑器与带宽参数上的贝叶斯先验相结合,来估计空间或属性变量的概率密度函数。带宽的后验分布将不确定性传播到最终的密度估计中,而不是将带宽视为固定的调优常数。

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来源

  1. Hjort, N. L., & Glad, I. K. (1995). Nonparametric density estimation with a parametric start. The Annals of Statistics, 23(3), 882–904. DOI: 10.1214/aos/1176324627
  2. Kernel density estimation. Wikipedia. link

如何引用本页

ScholarGate. (2026, June 3). Bayesian Kernel Density Estimation. ScholarGate. https://scholargate.app/zh/spatial-analysis/bayesian-kernel-density-estimation

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ScholarGateBayesian Kernel Density Estimation (Bayesian Kernel Density Estimation). 于 2026-06-15 检索自 https://scholargate.app/zh/spatial-analysis/bayesian-kernel-density-estimation · 数据集: https://doi.org/10.5281/zenodo.20539026