Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Autokorelasi Spasial Global× | I Moran Lokal (LISA)× | |
|---|---|---|
| Bidang | Analisis Spasial | Analisis Spasial |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 1950 | 1995 |
| Pencetus≠ | P. A. P. Moran (Moran's I, 1950); generalized by Luc Anselin | Luc Anselin |
| Tipe≠ | Spatial statistic / hypothesis test | Local spatial autocorrelation statistic |
| Sumber perintis≠ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Alias | global spatial dependence, global Moran's I, GSA, global spatial clustering measure | Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index |
| Terkait | 6 | 6 |
| Ringkasan≠ | Global Spatial Autocorrelation measures the degree to which similar values cluster together across an entire study area. Rather than identifying where clusters occur, it yields a single summary statistic — most commonly Moran's I — that quantifies whether spatial proximity coincides with value similarity, dissimilarity, or randomness across all observations simultaneously. | Local Moran's I, introduced by Luc Anselin in 1995, is a Local Indicator of Spatial Association (LISA) that decomposes global spatial autocorrelation into location-specific contributions. For every observation it produces a signed statistic and a significance value, enabling researchers to identify spatial clusters (high-high, low-low) and spatial outliers (high-low, low-high) on a map. |
| ScholarGateSet data ↗ |
|
|