Vidal-Sanz, Jose M.Universidad Carlos III de Madrid. Departamento de Economía de la Empresa2007-04-022009-04-012007-04-022009-04-012007-05https://hdl.handle.net/10016/680Corrected version in March 2009This 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.application/octet-streamapplication/octet-streamapplication/octet-streamtext/plainapplication/pdfengAtribución-NoComercial-SinDerivadas 3.0 EspañaSpatial dataSpectral densitySmoothing numberUniform asymptotic distributionBootstrapworking paperEmpresaopen accesswb072606