পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| গিয়ারির সি স্থানিক স্বয়ংসম্পর্ক (Geary's C Spatial Autocorrelation)× | গেটিস-অর্ড Gi* হট স্পট বিশ্লেষণ× | Spatial Lag Model (SAR / Spatial Autoregressive)× | |
|---|---|---|---|
| ক্ষেত্র | স্থানিক বিশ্লেষণ | স্থানিক বিশ্লেষণ | স্থানিক বিশ্লেষণ |
| পরিবার≠ | Hypothesis test | Regression model | Regression model |
| উদ্ভবের বছর≠ | 1954 | 1992 | 1988 |
| প্রবর্তক≠ | Roy C. Geary | Arthur Getis and J. Keith Ord | Anselin (textbook formalisation); LeSage & Pace |
| ধরন≠ | Global spatial autocorrelation statistic | Local spatial statistic | Spatial autoregressive regression |
| মৌলিক উৎস≠ | Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115–146. DOI ↗ | Getis, A. & Ord, J.K. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24(3), 189–206. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| অপর নাম≠ | Geary contiguity ratio, Geary's contiguity ratio, global spatial autocorrelation, Geary C mekânsal otokorelasyon | hot spot analysis, cold spot analysis, Gi* statistic, local Gi statistic | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| সম্পর্কিত≠ | 2 | 4 | 5 |
| সারসংক্ষেপ≠ | Geary's C is a global measure of spatial autocorrelation — whether nearby locations tend to have similar values — introduced by Roy Geary in 1954. Unlike Moran's I, which is built on the covariation of values around the mean, Geary's C is built on the squared differences between neighbouring values, making it more sensitive to local, short-range variation. Values below 1 indicate positive spatial autocorrelation (similar neighbours), near 1 indicate randomness, and above 1 indicate negative autocorrelation. | Getis-Ord Gi* is a local spatial statistic, introduced by Getis and Ord in 1992 and refined in 1995, that compares the value at each location and its neighbours against the global mean to identify statistically significant clusters of high values (hot spots) and low values (cold spots). | The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. |
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