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خانوادهRegression modelRegression model
سال پیدایش19951950
پدیدآورHjort & Glad (1995); extended by various authors in Bayesian nonparametricsP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
نوعNonparametric density estimationSpatial statistic / exploratory spatial data analysis
منبع بنیادینHjort, N. L., & Glad, I. K. (1995). Nonparametric density estimation with a parametric start. The Annals of Statistics, 23(3), 882–904. DOI ↗Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
نام‌های دیگرBayesian KDE, BKDE, Bayesian nonparametric density estimation, Bayesian adaptive KDEspatial dependence, geographic autocorrelation, spatial clustering measure, SA
مرتبط55
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.Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.
ScholarGateمجموعه‌داده
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  3. PUBLISHED
  1. v1
  2. 2 منابع
  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Bayesian Kernel Density Estimation · Spatial Autocorrelation. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare