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

  • Jose Vidal-Sanz


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.

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Article provided by Springer in its journal TEST.

Volume (Year): 18 (2009)
Issue (Month): 1 (May)
Pages: 96-114

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Handle: RePEc:spr:testjl:v:18:y:2009:i:1:p:96-114
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  1. Peter M. Robinson & J. Vidal Sanz, 2005. "Modified whittle estimation of multilateral models on a lattice," LSE Research Online Documents on Economics 4545, London School of Economics and Political Science, LSE Library.
  2. Jose M. Vidal-Sanz, 2007. "Automatic spectral density estimation for Random fields on a lattice via bootstrap," Business Economics Working Papers wb072606, Universidad Carlos III, Departamento de Economía de la Empresa.
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