Sizing up the regions of unique minima in the least squares nonlinear regression
Alternative metrics PlumXhttp://hdl.handle.net/11012/137267
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In nonlinear regression analysis, the residual sum of squares may possess multiple local minima. This complicates finding the global minimum and adversely affects reliability of the relevant statistical methods. Identifying and sizing up the regions of a readily identifiable global minimum (RIGM) is therefore of both theo- retical and practical interest. This paper addresses the issue by using equidistant function previously introduced by the first two co-authors of this paper.
Document typePeer reviewed
SourceMathematics for Applications. 2018 vol. 7, č. 1, s. 41-52. ISSN 1805-3629
- 2018/1