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| | Thin plate spline | Inverse distance weighting | Ordinary kriging | Universal kriging |
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| Description of the climate variability | Smoothed spline exactly through the measured spatial points | Straight line exactly through the measured spatial points | Smoothed line that best fits through the measured semivariance considering anisotropy | Smoothed line that best fits through the measured semivariance considering spatial trend |
Performance parameters | Performance in spite of the changing spatial point configuration | Performs comparatively worse than the stochastic methods and shows improved performance in cross-validation with the increased number of spatial point observations | Performs comparatively better than other methods when the number of spatial point observations is too little but in general shows improved performance in cross-validation with the increased number of spatial point observations | Performs comparatively better than the deterministic methods and shows improved performance in cross-validation with the increased number of spatial point observations | Performs best of all the methods applied and shows improved performance in cross-validation with increased number of spatial point observations
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Measurement errors’ inclusion | Includes measurement errors partially in results because of the minimal smoothing | Includes measurement errors in results totally | Excludes measurement errors in result by smoothing | Excludes measurement errors in result by smoothing |
Short versus long range variability | Describes mostly long range variability by removing the noise of short range variability | Describes only short range variability | Adjusts between the short and long range variability by incorporating anisotropy and semivariance | Describes mostly long range variability in light of the spatial trend
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