A Comparison of Linear and Nonlinear Random Field Estimators
Scanning notes: Disclaimer inserted for illegible graphs and text.
| Main Authors: | , |
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| Published: |
Cambridge, Mass. : Ralph M. Parsons Laboratory, Hydrology and Water Resource Systems, Massachusetts Institute of Technology, Dept. of Civil Engineering
2022
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| Online Access: | https://hdl.handle.net/1721.1/143020 |
| _version_ | 1826206566450200576 |
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| author | Angulo, Carlos Enrique Puente Bras, Rafael L. |
| author_facet | Angulo, Carlos Enrique Puente Bras, Rafael L. |
| author_sort | Angulo, Carlos Enrique Puente |
| collection | MIT |
| description | Scanning notes: Disclaimer inserted for illegible graphs and text. |
| first_indexed | 2024-09-23T13:34:40Z |
| id | mit-1721.1/143020 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:34:40Z |
| publishDate | 2022 |
| publisher | Cambridge, Mass. : Ralph M. Parsons Laboratory, Hydrology and Water Resource Systems, Massachusetts Institute of Technology, Dept. of Civil Engineering |
| record_format | dspace |
| spelling | mit-1721.1/1430202022-06-14T03:20:35Z A Comparison of Linear and Nonlinear Random Field Estimators Angulo, Carlos Enrique Puente Bras, Rafael L. Scanning notes: Disclaimer inserted for illegible graphs and text. Prepared with support of National Science Foundation and Office of Surface Mining through Grants CME-7919836 G5105071 The estimation of random fields from limited samples is an important issue in most fields of geophysics, such as Hydrology and Meteorology. Work by Matheron and others at the Paris School of Mines has popularized Kriging techniques to estimate random fields at specified locations or to get areal averages. This work presents the theoretical and practical aspects of both Linear and Nonlinear (Disjunctive) Kriging estimators, and provides a comparison of their performance in estimating point and areal values of generated fields. The experiments performed were designed to closely resemble actual and practical situations. The results show that small sample based inconsistencies lead to a Disjunctive Kriging solution which does not give more accurate estimates than the theoretically less precise Linear Kriging estimator. The results also suggest the use of a multi-realization approach when using these techniques in network design problems. 2022-06-13T13:10:12Z 2022-06-13T13:10:12Z 1982-11 287 https://hdl.handle.net/1721.1/143020 10422941 241273 R (Massachusetts Institute of Technology. Department of Civil Engineering) ; 82-51. Report (Ralph M. Parsons Laboratory for Water Resources and Hydrodynamics) ; 287. application/pdf Cambridge, Mass. : Ralph M. Parsons Laboratory, Hydrology and Water Resource Systems, Massachusetts Institute of Technology, Dept. of Civil Engineering |
| spellingShingle | Angulo, Carlos Enrique Puente Bras, Rafael L. A Comparison of Linear and Nonlinear Random Field Estimators |
| title | A Comparison of Linear and Nonlinear Random Field Estimators |
| title_full | A Comparison of Linear and Nonlinear Random Field Estimators |
| title_fullStr | A Comparison of Linear and Nonlinear Random Field Estimators |
| title_full_unstemmed | A Comparison of Linear and Nonlinear Random Field Estimators |
| title_short | A Comparison of Linear and Nonlinear Random Field Estimators |
| title_sort | comparison of linear and nonlinear random field estimators |
| url | https://hdl.handle.net/1721.1/143020 |
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