Density estimation for spatial-temporal models

• Liliana Forzan ^[2] ; Ricardo Fraiman ^[1] ; Pamela Llop ^[2]
  1. [1] Universidad de San Andrés

     Universidad de San Andrés

     Argentina

     
  2. [2] UNL-CONICET
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 22, Nº. 2, 2013, págs. 321-342
• Idioma: inglés
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• Resumen

  • In this paper a k-nearest neighbor type estimator of the marginal density function for a random field which evolves with time is considered. Considering dependence, the consistency and asymptotic distribution are studied for the stationary and nonstationary cases. In particular, the parametric rate of convergence T−−√ is proven when the random field is stationary. The performance of the estimator is shown by applying our procedure to a real data example.