ETH Zürich /Computer Science /Publications
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Deutsche Version ETH Zürich /Computer Science /Publications Search |
Erwin Achermann, Oscar Chinellato, Institute of Scientific Computing, ETH Zürich
| Keywords: | Function Fitting, EIV, Measurement Uncertainty, Calibration |
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| Language: | English |
| Pages: | 14 |
| Available Files: | abstract portable document format (PDF) plain Postscript gnu-compressed PDF gnu-compressed PS |
| Abstract: |
Most analytical methods are relative and hence require calibration.
Calibration measurements are normally performed with reference
materials or calibration standards. Typically least squares methods
have been employed in such a manner as to ignore uncertainties
associated with the calibration standards. However different
authors have shown that by taking into account the uncertainties associated
with the calibration standards, better approximations to the model
are possible. We show a complete, numerically stable and fast way to compute the "Maximum Likelihood (fitting of a) Functional Relationship" (MLFR). |
Jul . 2000
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