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Such models usually do not yield closed formulas for maximum likelihood estimates, hence numerical methods such as the well-known Fisher scoring or Expectation Maximization (EM) algorithms are used in practice.
Here, we cannot obtain such estimates, hence we rely on parameter estimates from other empirical studies.
The proposed algorithm incorporates a forgetting factor to discard the old unreliable estimates, hence achieving better convergence performance.
Obtained k ave = 47.3 mD is approximately close to the BHP estimates, hence a good estimate of the fluid-phase permeabilities.
Andersson et al. [1] also concluded that the spatial dependence would only have a negligible effect on the welfare estimates, hence the OLS and the spatial-lag model revealed similar estimates of marginal WTP.
Urban areas and other districts were over-sampled for correct population estimates, hence more data points in some areas than others.
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On the contrary, the GCE-BEM produces a full channel matrix estimate: Hence, this choice permits to increase the equalizer bandwidth, so that the number of equalizer diagonals can exceed the number of BEM parameters.
However, this is at the cost of (i) increasing the computational expense of the algorithm and (ii) making the algorithm less likely to converge to a ML estimate, hence reducing the number of target events located.
When (sigma =frac{2}{n+1}), the point P coincides with the endpoint at which we want to prove restricted weak type estimate, hence in this case, interpolating in the above way does not help.
Note that the az-el system has no possibility of inconsistency, but for the special cases of φ = {0,π} the angle θ cannot be estimated (hence, the 2-D CRLB does not exist).
They suggested that short internal branches and long terminal branches reduces the accuracy with which a phylogeny can be estimated, hence the resolution that can be obtained.
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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