Automatic spectral density estimation for Random fields on a lattice via bootstrap

Jose Vidal-Sanz

DEE - Working Papers. Business Economics. WB from Universidad Carlos III de Madrid. Departamento de Economía de la Empresa

Abstract: This paper considers the nonparametric estimation of spectral densities for second order stationary random fields on a d-dimensional lattice. I discuss some drawbacks of standard methods, and propose modified estimator classes with improved bias convergence rate, emphasizing the use of kernel methods and the choice of an optimal smoothing number. I prove uniform consistency and study the uniform asymptotic distribution, when the optimal smoothing number is estimated from the sampled data.

Keywords: Spatial; data; Spectral; density; Smoothing; number; Uniform; asymptotic; distribution; Bootstrap (search for similar items in EconPapers)
Date: 2007-05
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:cte:wbrepe:wb072606

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