This title appears in the Scientific Report :
2017
Please use the identifier:
http://dx.doi.org/10.1002/elsc.201700022 in citations.
Kriging with trend functions nonlinear in their parameters: Theory and application in enzyme kinetics
Kriging with trend functions nonlinear in their parameters: Theory and application in enzyme kinetics
Kriging is an interpolation method commonly applied in empirical modeling for approximating functional relationships between impact factors and system response. The interpolation is based on a statistical analysis of given data and can optionally include a priori defined trend functions. However, Kr...
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Personal Name(s): | Freier, Lars |
---|---|
Wiechert, Wolfgang / von Lieres, Eric (Corresponding author) | |
Contributing Institute: |
Biotechnologie; IBG-1 |
Published in: | Engineering in life sciences, 17 (2017) 8, S. 916–922 |
Imprint: |
Weinheim
Wiley-VCH
2017
|
DOI: |
10.1002/elsc.201700022 |
Document Type: |
Journal Article |
Research Program: |
Innovative Synergisms |
Publikationsportal JuSER |
Kriging is an interpolation method commonly applied in empirical modeling for approximating functional relationships between impact factors and system response. The interpolation is based on a statistical analysis of given data and can optionally include a priori defined trend functions. However, Kriging can so far only be used with trend functions that are linear with respect to the parameters. In this contribution, we present an extension of the Kriging approach for handling trend functions that are nonlinear in their parameters. Our approach is based on Taylor linearization combined with an iterative parameter estimation procedure whose solution is practically computed via a root finding problem. We demonstrate our novel approach with measurement data from the application field of biocatalysis. |