國立東華大學應用數學系

專    題    演    講

主講人：陳春樹

         彰化師範大學統計資訊研究所

講  題：Estimation and Prediction of Geostatistical Regression Models via a Corrected SURE

時  間：104 年 05月 08 日 (星期五)  15:00-17:00

地  點：理工一館 A324 會議室

摘 要

We consider geostatistical regression models to predict spatial variables of interest and the model parameters are estimated by the likelihood-based methods. It is known that the covariance parameters cannot be estimated well even when increasing amounts of data are collected densely in a fixed domain, and hence the prediction would be inaccurate. Although a best linear unbiased predictor has been used when model parameters are known, a predictor after plugging-in estimated parameters is nonlinear and hence may be not the best in practice. Therefore, we propose an adjusted covariance parameter estimation method via minimizing a corrected Stein’s unbiased risk estimator. The resulting adjusted parameter estimators perform better than the conventional likelihood-based estimators, and the spatial predictor is more accurate and stable. Statistical inference for the proposed method is justified both theoretically and numerically. Finally, a real data example regarding the arsenic concentration of groundwater in Bangladesh is applied for illustration.

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