ScholarGate
Asistent

Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Bayesovský odhad hustoty jádra×Lokální kriging (kriging s pohyblivým oknem)×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku19951990
TvůrceHjort & Glad (1995); extended by various authors in Bayesian nonparametricsHaas, T. C.
TypNonparametric density estimationSpatial interpolation (local variant)
Původní zdrojHjort, N. L., & Glad, I. K. (1995). Nonparametric density estimation with a parametric start. The Annals of Statistics, 23(3), 882–904. DOI ↗Haas, T. C. (1990). Kriging and automated variogram modeling within a moving window. Atmospheric Environment, 24(7), 1759-1769. DOI ↗
Další názvyBayesian KDE, BKDE, Bayesian nonparametric density estimation, Bayesian adaptive KDEmoving-window kriging, local kriging interpolation, windowed kriging, neighborhood kriging
Příbuzné53
ShrnutíBayesian 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.Local Kriging is a spatially adaptive geostatistical interpolation method that restricts each prediction to a moving neighborhood of nearby observations, fitting a variogram model locally within that window. This allows spatial covariance structure to vary across the study region rather than imposing a single global variogram, making it better suited to large or non-stationary spatial fields.
ScholarGateDatová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED

Přejít na hledání Stáhnout prezentaci

ScholarGatePorovnat metody: Bayesian Kernel Density Estimation · Local Kriging. Získáno 2026-06-15 z https://scholargate.app/cs/compare