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Income approximations were based on data from the German federal statistics bureau.
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Causal approximations are based on the idea that more approximate descriptions usually explain less about a phenomenon than more accurate descriptions.
The approximations are based on a local interpolation scheme and on an efficient simulation technique.
The PCE approximations are based on rigorous mathematical concepts developed from functional analysis and measure theory.
These approximations are based on the structure and the internal capacitive coupling of SOI-FinFET.
The proposed approximations are based on certain physical assumptions which simplify the underlying characteristic equation to be solved.
Our approximations are based on the two finite difference methods for discretizing delta functions presented in [16].
The justification for the use of these approximations is based on a significant reduction in computational time by not requiring direct numerical integration, and the fact that only the first two moments of the distribution are known.
The construction of these approximations is based on a sequence of I.I.D. random variables.
Approximations are based on an exchange rate of US$1.00 to GHC3.50 (Ghana Cedis) as at March, 2015.
Such approximations are based on a smart use of Laplace or other related analytical approximations and of numerical integration schemes.
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