Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Beiešiskais Morana I× | Moran's I× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1950 / 2000s | 1950 |
| Autors≠ | Moran (1950), Bayesian extension developed in spatial statistics literature (late 1990s–2000s) | Patrick A. P. Moran |
| Tips≠ | Bayesian spatial autocorrelation test | Spatial autocorrelation statistic |
| Pirmavots≠ | Haining, R. (2003). Spatial Data Analysis: Theory and Practice. Cambridge University Press. ISBN: 9780521774611 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Citi nosaukumi | Bayesian spatial autocorrelation test, Bayesian Moran statistic, Moran's I under Bayesian inference, Bayesian global spatial association | Moran's I statistic, global Moran's I, spatial autocorrelation index, Moran index |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Bayesian Moran's I embeds the classical Moran's I spatial autocorrelation test within a Bayesian probabilistic framework. Rather than producing a single p-value, it yields a posterior distribution over the spatial autocorrelation parameter, enabling uncertainty quantification, incorporation of prior knowledge, and more principled inference in small or irregular spatial datasets. | Moran's I is the standard global statistic for detecting spatial autocorrelation: whether nearby locations tend to share similar values. The index ranges from approximately −1 (perfect dispersion) through 0 (spatial randomness) to +1 (perfect clustering), allowing researchers to test whether a geographic pattern differs from complete spatial randomness with a single, interpretable number. |
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