Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Moran's I Ruang-Waktu× | Indikator Lokal Asosiasi Spasial (LISA)× | |
|---|---|---|
| Bidang | Analisis Spasial | Analisis Spasial |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 1981 | 1995 |
| Pencetus≠ | Cliff & Ord (extended to space-time domain) | Luc Anselin |
| Tipe≠ | Spatial autocorrelation statistic | Local spatial statistic |
| Sumber perintis≠ | Cliff, A. D., & Ord, J. K. (1981). Spatial Processes: Models and Applications. Pion. ISBN: 978-0850860818 | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Alias | space-time autocorrelation index, ST Moran's I, spatiotemporal Moran's I, space-time I statistic | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Terkait≠ | 5 | 6 |
| Ringkasan≠ | Space-Time Moran's I extends the classic Moran's I statistic into the spatiotemporal domain, measuring whether observations that are close in both space and time tend to be more similar than those that are distant. It detects clustering, dispersion, or randomness across a combined space-time weight matrix, making it a foundational tool in epidemiology, criminology, and environmental monitoring. | LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence. |
| ScholarGateSet data ↗ |
|
|