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Box dimension estimation of multi-dimensional random fields via wavelet shrinkage

机译:基于小波收缩的多维随机域盒维估计

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Computation of the box dimension for high-dimensional surfaces is much more complicated than the one-dimensional case. To obtain a fast computation, we employ the relationship between the box dimension and the wavelet coefficients of a surface through the local oscillation. This approach gives an appropriate consistent estimator of box dimension for noisy paths. The behavior of convergence is also studied under H?lder continuity assumption for the family of index-$eta$ Gaussian fields. We show that the precision of the estimation procedure is not affected by the growth of dimension of the sample path. We finally examine the properties of the proposed estimator using a simulation study and a real dataset on equlibration of a particular solution.
机译:高维表面的盒子尺寸的计算要比一维情况复杂得多。为了获得快速的计算,我们通过局部振荡利用盒子尺寸和表面的小波系数之间的关系。这种方法可以为嘈杂的路径提供适当的箱形尺寸估计。在H $ lder连续性假设下,对索引为$ beta $的高斯场族也研究了收敛的行为。我们表明,估计过程的精度不受样本路径维数增长的影响。最后,我们使用仿真研究和关于特定解决方案均衡的真实数据集,检验了所提出估计量的性质。

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