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Under suitable conditions, we obtain expansions for the bias and the variance of wavelet estimator, prove the moment consistency, the strong consistency, the strong convergence rate of it, and establish the asymptotic normality of wavelet estimator.
Under suitable conditions, we obtain expansions for the bias and the variance of wavelet estimators ˆβn and ˆgn of β and g respectively, prove their weak consistency, and establish the asymptotic normality and the Berry Esseen bound of ˆβn.
Without considering I2, the obtained expansion seems overestimated and could generate some misleading results.
Lack of obtained expansion, in addition to late relapse after splint removal, can result in relapse of the posterior crossbite.
We compare our method with traditional methods based on the total cost of the obtained expansion plans.
end{aligned} Clearly, the 'size' of the set (mathcal{F}_{g}) reflects the flexibility of the function g in regard of obtaining expansions of type (1.1).
As a consequence, we obtain asymptotic expansion of the Wallis sequence.
Using the orthonormal property of the KLT-basis system, we obtain the expansion coefficients as (4).
One can obtain volume expansion of materials with the data of lattice parameters at different temperature.
Here, we obtain an expansion for the quantity f(x;δ,α,ξ)F x;δ,α,ξ) c.
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CEO of Professional Science Editing for Scientists @ prosciediting.com