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| كرِيجة الزمكان× | الكْرِيجَة الشاملة (الكْرِيجَة مع اتجاه)× | |
|---|---|---|
| المجال | التحليل المكاني | التحليل المكاني |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1999 | 1969 |
| صاحب الطريقة≠ | Cressie & Huang; Kyriakidis & Journel | Georges Matheron |
| النوع≠ | Geostatistical interpolation | Geostatistical interpolation with spatial trend |
| المصدر التأسيسي≠ | Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340. DOI ↗ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ |
| الأسماء البديلة | spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time | kriging with a trend, kriging with drift, trend kriging, evrensel kriging |
| ذات صلة≠ | 4 | 3 |
| الملخص≠ | Space-Time Kriging is a geostatistical interpolation method that predicts an unknown variable at any location and time by borrowing strength from nearby observations in both space and time simultaneously. It models the joint spatial-temporal covariance structure through a space-time variogram, then uses optimal linear weights to produce predictions with quantified uncertainty. | Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances. |
| ScholarGateمجموعة البيانات ↗ |
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