Stochastically established resolution analysis helps to determine empirical tuning parameters in general interpolation schemes

• Main Authors: Zhi-Yu Ye, 葉治宇
• Other Authors: 喬凌雲
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/77496730350841735354

碩士 === 國立臺灣大學 === 海洋研究所 === 102 === Resolution analysis has been a crucial appraisal procedure in general estimation problems to help with the correct interpretation. However, complete resolution information is usually inaccessible due to the sizeable matrix inversion involved with the construction of the resolution matrix. Furthermore, there are not explicit forward kernels embedded within formulations for popular interpolation algorithms such as the Kriging and the minimum curvature gridding schemes. Stochastic simulation has been proposed to make the resolution evaluation for sizeable inverse problems tractable. We generalize the method of getting resolution information for the popular interpolation schemes. Furthermore, there are usually certain empirically determined tuning parameters involved in these interpolation schemes, for example, the ideal function and influence range for fitting the semi-variogram in the Kriging method and the tension parameter in the minimum curvature gridding scheme. In this study, we will show that our proposed resolution analysis not only provide the crucial spatial resolution variation, more importantly, it helps to determine those critical tuning parameters that have been determined empirically and arbitrarily.