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
DOI: 10.1007/s11749-012-0313-3
Texto completo no disponible (Saber más ...)
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.