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Central limit theorems and minimum-contrast estimators for linear stochastic evolution equations

机译:线性随机演化方程中央限制定理和最小对比度估计

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Central limit theorems and asymptotic properties of the minimum-contrast estimators of the drift parameter in linear stochastic evolution equations driven by fractional Brownian motion are studied. Both singular ( and regular ( types of fractional Brownian motion are considered. Strong consistency is achieved by ergodicity of the stationary solution. The fundamental tool for the limit theorems and asymptotic normality (shown for Hurst parameter ) is the so-called 4th moment theorem considered on the second Wiener chaos. This technique provides also the Berry-Esseen-type bounds for the speed of the convergence. The general results are illustrated for parabolic equations with distributed and pointwise fractional noises.
机译:研究了分数褐色运动驱动的线性随机演化方程中漂移参数的最小对比度估计的中央极限定理和渐近性。 奇异(和常规(分数褐色运动的类型)。通过静止解决方案的遍历,实现了强的一致性。限制定理和渐近常态的基本工具(显示为赫斯特参数)是所谓的第4矩定理 在第二个Wiener混乱。该技术还提供了贝瑞 - esseen类型的速度,用于换档的速度。将一般结果用于分布式和尖分数噪声的抛物线方程。

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