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In order to relax these requirements, we show that only first order moments of these distributions need to be known if the time between samples is large, or individuals from all age classes which reproduce are sampled.
A main merit of this method is that it can approximate implicit failure functions well as the number of samples is large enough due to the features of the correct classification of all samples.
When the number of samples is large, and are close.
Hence, computing the similarity measures is expensive if the number of samples is large.
More specifically, let us consider Fisher's transformation z = 1 2 ln 1 + r 1 − r = artanh ( r ) (8). and assume that the number of samples,, is large.
When the number of samples is large enough, the estimated probability can be close enough to the actual posteriori probability density function, reaching the result of the optimal Bayesian estimation [21].
Similar(42)
Thus, the saturation magnetization of the corresponding samples is larger.
Obviously, the particle size for the all current Ni samples is larger than this value.
The impedance of the polished coated samples is larger than bare lead, but not larger than corroded lead.
From the analysis of Figure 2, the grain size for annealed samples is larger than the as-deposited one.
Some surgical samples were large enough to enable us to study several different tissues.
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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