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Because the analytical form of the marginal distribution is not available, we hereby perform an approximate (Monte Carlo) marginalization by sampling from the joint posterior distribution of the states and the parameters.
Though the marginal distribution is restricted to the beta distribution, the proposed approach is simple and efficient.
Moreover, all the steganalytic algorithms using the first-order statistics of cover image are not efficient because the marginal distribution is inherently preserved by the algorithm.
Internet traffic packet interarrival times are very well modeled by an MFSD in which the marginal distribution is Weibull; this is validated by extensive model checking for 715,665,213 measured arrival times on three Internet links.
Then, a simple but effective model based on a marginal distribution is used for the local temporal context of adjacent strokes in order to improve the sequence labeling result.
A copula is a multivariate joint distribution defined on the n-dimensional unit cube [0,1] n in a way that every marginal distribution is uniform in the interval [0,1].
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Homogeneity of the marginal distribution was not fulfilled (P<0.0001); the level of self reported physical activity fell during the period from pre-illness to baseline for both the intervention and control group.
The median for both marginal distributions is 10.
In the case of the MECC application, the impact of the marginal distributions is eliminated.
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.
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].
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