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This paper presents a theoretical model of errors of probes for CNC machine tools.
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A systemic model of error causation is propagated and subsequently used to develop a learning framework for design error prevention.
Based on the detailed analysis of systematic errors, mathematical model of error parameters is constructed and linear calibration method is proposed for magnetic gradient tensor system.
Drawing on 18 months of participant observations and 38 interviews conducted in a Big 4 accounting firm, we develop a multi-level model of error management.
Each has its model of error causation and each model gives rise to quite different philosophies of error management [ 17].
The technology-specific component utilizes an intensity-dependent model of error derived from numerous self-self hybridizations.
The PEP manual, which is available at http://joyx.joensuu.fi/∼ek/pep/pep.htm PEP, contains a technical description of the scaled model of error.
The scaled model of error assumes that the rates are normal in the log scale and net-migration numbers are normal in the original scale.
This appendix gives an informal explanation of the main characteristics of the scaled model of error, as it is implemented in the computer program Program for Error Propagation (PEP).
We compared the theoretical p-value and statistical power drawn from the Geary-Hinkley transformation against the p-value and statistical power computed from simulations relying on several different model of error and distributions.
Standards and modeling of errors, however, offer nearer-term help.
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