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Mass discharge measurement error was investigated using a Monte Carlo modeling analysis as a function of the contaminant plume position and width, and as a function of the pumping conditions used in the different pumping tests.
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Possible inflation of the type I error rate due to population stratification was investigated using genomic control [ 31].
Residual variability was investigated using proportional, additive, or combined proportional and additive error models.
Non-linearity was investigated using quadratic terms.
Metabolic stability was investigated using radio-HPLC.
Their performance in terms of pairwise error probability is investigated using maximum likelihood detection and decoding.
For single systems the notion of quasi-input-to-state dynamical stability (quasi-ISDS) for reduced-order observers is introduced and observers are investigated using error Lyapunov functions.
Relationship between the occurrence of errors and potential risk factors were investigated using logistic regression models with random effects.
The frame error rate (FER) performance of the proposed protocol is investigated using Monte Carlo simulations.
The error characteristics and stability properties of the interpolation kernels are investigated using Fourier analysis.
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