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.
Year of publication: |
2007-05
|
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Authors: | Vidal-Sanz, Jose M. |
Institutions: | Departamento de EconomÃa de la Empresa, Universidad Carlos III de Madrid |
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