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Quality controlling of the geologic model for errors and problems.
We construct a lemniscate model for errors to find multivariate outliers with the Mahalanobis distance.
For the construction of a model, the following steps were followed: Quality controlling of the geologic model for errors and problems.
However, I have already shown that the main results are very similar with the current model for errors to the case when there is no error at all (ε = 0.05 and ε = 0 in Tables 2 and 3).
We derive an integer linear programming solution to the VAF factorization problem in the case of error-free data and extend this solution to real data with a probabilistic model for errors.
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Subsequently, a mathematical model for error evaluation is built.
The work presents integrated model for error attenuation of smart toolpost under different design parameters.
Scheme I uses only the hydrological model, while scheme II includes an AR model for error correction.
The method is based on the so-called scaled model for error, implemented in the program Program for Error Propagation (PEP).
The theoretical frame for such a program can be built on quasispecies theory, a general evolutionary model for error-prone self replicative systems, first introduced by Eigen.
We next take a closer look at the finite population model for error rates between the error-threshold of the infinite population model and that of the finite population model.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com