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A comparison of sampling grids, cut-off distance and type of residuals in parametric variogram estimation

机译:参数变异函数估计中采样网格,截止距离和残差类型的比较

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In spatial statistics, the correct identification of a variogram model when fitted to an empirical variogram depends on many factors. Here, simulation experiments show fitting based on the variogram cloud is preferable to that based on Matheron's and Cressie-Hawkins empirical variogram estimators. For correct model specification, a number of models should be fitted to the empirical variogram using a grid of cut-off values, and recommendations are given for best choice. A design where roughly half the maximum distance between points equals the practical range works well for correct variogram identification of any model, with varying nugget sizes and sample sizes.
机译:在空间统计中,对拟合后的方差图模型进行正确识别取决于许多因素。在此,仿真实验表明,基于方差图云的拟合优于基于Matheron和Cressie-Hawkins经验方差图估计量的拟合。为了获得正确的模型规格,应使用截止值的网格将多个模型拟合到经验变异函数,并给出最佳选择的建议。点与点之间最大距离的大约一半等于实际范围的设计可以正确地识别任何模型,并且可以改变块金大小和样本大小。

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