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which has a singular component along the line x 1=x 2 and meets (3).
The construction in Example 3 incorporates a singular component into the resulting distribution, which belongs to a wider class of Extended Marshall Olkin (EMO) bivariate distributions introduced by Pinto and Kolev (2015b).
In fact, we do not exclude the possibility of existence of a singular component along the line L={x 1=x 2≥0}, i.e. it may happen that P(X 1=X 2)>0.
The joint distribution is absolutely continuous if and only if (phantom {dot {i}!}a_{0} = r_{X_{1}}(0) + r_{X_{2}}(0)), otherwise it possesses a singular component.
We got two extensions of the Gumbel's type I distribution: one being absolutely continuous and the other having a singular component, represented by (19) and (20) respectively, consult Remark 6 as well.
In Sections 2.2 and 2.3, P R can be chosen as the distribution of any non-negative random variable thus ({frac {dP^{R}}{dnu }}) being a mixture of an absolutely continuous, a discrete and a singular component, in general.
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We suggest that this paradigm, therefore, has limited ability to address emergent risks implicit in the whole system rather than any singular component.
We give applications to the case of perturbations of the Laplace operator by a positive Radon measure with a nontrivial singular component.
It is possible that the transfer function may have a nontrivial singular component (i.e. a nontrivial everywhere analytic term) as discussed in Section 5.1, in which case the zero-pole interpolation may not reproduce a converging sequence of approximations to the given transfer function (T z)).
Each singular component consists of a singular value (a scalar), right singular vector (r-SV) and left singular vector (l-SV).
In fact, most substitutions are disfavored by the first singular component of a PSSM.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com