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Let V be a random vector with an arbitrary distribution over R n.
Let X be a random vector with a partial differentiable sf F̄.
[ 41 ] The Crypto Lemma Let V be a random vector with an arbitrary distribution over (mathbb {R}^{n}).
Let X= X1,X2,X3) be a random vector from the multinomial distribution given by (n,p1,p2,p3).
Let x 0 be a random vector in H 1 where every element of x 0 is in ( 0, 1 ).
Let X 1,…,X n be a random vector of random variables independent and identically distributed where each variable follows an unknown distribution, denoted by f.
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Let (mathbf{X}=(X_{1},dots,X_{n})) be a random vectors with sf F̄.
In turn, these general notions give rise to "randomness diagrams"—tangible planar visualizations that answer the question: How random is a random vector?
(overrightarrow{{a}}) is directly diminished from 2 to 0. (overrightarrow{r}) is a random vector [0, 1].
Referring to the analysis in Section 2, the -dimensional vector, with the numbers of decisions received by the FCs, is a random vector.
where U = (u1,…,u n ) T is a random vector and P U VV) (resp. p u i ( v i ) ) are the joint, (resp. marginal), PDF.
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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