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Sharp convergence rates for fixed design regression estimators for negatively associated random variables are established.
Once they started playing, though, there was a sharp convergence from what separates them physically with both players hitting some fierce blows off the ground.
For a family of second-order parabolic systems with bounded measurable, rapidly oscillating and time-dependent periodic coefficients, we investigate the sharp convergence rates of weak solutions in L2.
In all graphs, we observe that either classical operator has sharp convergence or both operators behave alike after a large number of iterations.
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We establish the sharp O convergence rate in Wm−1,p0 with p0= 2dd−1 in a bounded Lipschitz domain in Rd as well as the uniform large-scale interior Cm−1,1 estimate.
Our results include a sharper theoretical convergence result for p-Laplacian systems compared to what may be found in existing works.
According to our analysis, the preconditioning not only reduces the eigenvalue ratio from O(1/(h⋅hmin) to O(h−2), but also keeps the sharp second order convergence.
Estimated diffusion tensors at this high resolution were able to capture complex fiber configurations such as sharp curves, and convergence and divergence of tracts, but were unable to resolve directions at sites of crossing fibers.
We prove that our estimation attains a sharp rate of convergence and show the optimality.
Proposition 1, which is a corollary of Lemma 10, contains several sharp results about convergence of (Y^{s}(n)).
Izenman and Tran ([1], 1990) discussed the uniform consistency and sharp rates of convergence under strong mixing and absolute regularity conditions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com