Automatic spectral density estimation for Random fields on a lattice via bootstrap
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.
|Date of creation:||May 2007|
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- Jose Vidal-Sanz, 2009.
"Automatic spectral density estimation for random fields on a lattice via bootstrap,"
TEST: An Official Journal of the Spanish Society of Statistics and Operations Research,
Springer, vol. 18(1), pages 96-114, May.
- 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.
- Robinson, P.M. & Vidal Sanz, J., 2006.
"Modified Whittle estimation of multilateral models on a lattice,"
Journal of Multivariate Analysis,
Elsevier, vol. 97(5), pages 1090-1120, May.
- 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.
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