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The vector of SK weights was given by (Olea 1999), λT = c k,d c d,d 1, [2] where c k,d = c X(p k, p d) is a row vector of covariance for X(p ) between the estimation point and data points, and c d,d = c X(p d, p d) is a covariance matrix for X(p ) between the data points.
Similar(59)
Each area is weighted by importance (approximate weights are given below).
In the discrete case the weights are given by the probability mass function, and in the continuous case the weights are given by the probability density function.
and the weights are given by (19).
Some applications in different weights are given.
Equal weights were given to scalar and vector measurements.
The expression of the weights is given by (35).
The optimal array weights are given by (31).
where the so-called importance weights are given by (12).
Effects of the geometry selection on the frames' seismic behaviours and weights are given.
In the protocol learning, larger weights are given to the visual features that are spatiotemporally consistent.
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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