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Furthermore, maximum achievable kappa values (κ max) given the marginal distributions are reported, to determine how much of the marginally permitted agreement is present between raters [13].
The marginal distributions are described by Generalized Pareto laws.
This problem can be difficult even when the marginal distributions are known.
Abstract: Several examples are discussed where properties or origins of marginal distributions are used to determine a joint distribution.
For the systems considered excellent results over the main body and tails of the marginal distributions are obtained.
A Lévy process based on this multivariate infinitely divisible distribution is known as Laplace motion, and its marginal distributions are multivariate generalized Laplace laws.
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On image reconstruction, a generative Gabor model with fitted marginal distributions is shown to significantly outperform a Gabor model with uniformly sampled parameters.
The inverse problem is to determine whether a set of fragmentary probabilities or marginal distributions is conformable in the sense that there exists a probability space or joint distribution that yields these fragmentary probabilities or marginal distributions.
The median for both marginal distributions is 10.
In the case of the MECC application, the impact of the marginal distributions is eliminated.
If the marginal distributions were not affected by the confounder, we could pool the N k data together to yield a test based on the usual estimate (hat {kappa }) calculated on the whole dataset.
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