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حوزهتحلیل فضاییتحلیل فضایی
خانوادهRegression modelRegression model
سال پیدایش19951990
پدیدآورHjort & Glad (1995); extended by various authors in Bayesian nonparametricsHaas, T. C.
نوعNonparametric density estimationSpatial interpolation (local variant)
منبع بنیادینHjort, 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 ↗
نام‌های دیگرBayesian KDE, BKDE, Bayesian nonparametric density estimation, Bayesian adaptive KDEmoving-window kriging, local kriging interpolation, windowed kriging, neighborhood kriging
مرتبط53
خلاصهBayesian 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.
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ScholarGateمقایسهٔ روش‌ها: Bayesian Kernel Density Estimation · Local Kriging. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare