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क्षेत्रस्थानिक विश्लेषणस्थानिक विश्लेषण
परिवारRegression modelRegression model
उद्भव वर्ष19951950
प्रवर्तकHjort & 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)
प्रकारNonparametric density estimationSpatial statistic / exploratory spatial data analysis
मौलिक स्रोतHjort, 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 ↗
उपनामBayesian KDE, BKDE, Bayesian nonparametric density estimation, Bayesian adaptive KDEspatial dependence, geographic autocorrelation, spatial clustering measure, SA
संबंधित55
सारांशBayesian 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.
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  3. PUBLISHED

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ScholarGateविधियों की तुलना करें: Bayesian Kernel Density Estimation · Spatial Autocorrelation. 2026-06-15 को यहाँ से प्राप्त https://scholargate.app/hi/compare