Premium
Variance Reduction Analysis
Author(s) -
Rouhani Shahrokh
Publication year - 1985
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr021i006p00837
Subject(s) - variance reduction , ranking (information retrieval) , kriging , reduction (mathematics) , variance (accounting) , statistics , mathematics , function (biology) , stability (learning theory) , extension (predicate logic) , sampling (signal processing) , sequence (biology) , computer science , mathematical optimization , algorithm , artificial intelligence , monte carlo method , machine learning , genetics , geometry , accounting , filter (signal processing) , evolutionary biology , business , computer vision , biology , programming language
This paper presents an algorithm for optimal data collection in random fields, the so‐called variance reduction analysis, which is an extension of kriging. The basis of variance reduction analysis is an information response function (i.e., the amount of information gain at an arbitrary point due to a measurement at another site). The ranking of potential sites is conducted using an information ranking function. The optimal number of new points is then identified by an economic gain function. The selected sequence of sites for further sampling shows a high degree of stability with respect to noisy inputs.