Regression modelGIS / spatial

Bayesian Kernel Density Estimation

Bayesian Kernel Density Estimation (BKDE) is a nonparametric method for estimating the probability density function of a spatial or attribute variable by combining a kernel smoother with a Bayesian prior over the bandwidth parameter. The posterior distribution of the bandwidth propagates uncertainty into the final density estimate rather than treating the bandwidth as a fixed tuning constant.

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Sources

  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

Related methods

ScholarGateBayesian Kernel Density Estimation (Bayesian Kernel Density Estimation). Retrieved 2026-06-04 from https://scholargate.app/tr/spatial-analysis/bayesian-kernel-density-estimation