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Density estimation for spatial-temporal models

Author

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  • Liliana Forzani
  • Ricardo Fraiman
  • Pamela Llop

Abstract

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 $\sqrt{T}$ is proven when the random field is stationary. The performance of the estimator is shown by applying our procedure to a real data example. Copyright Sociedad de Estadística e Investigación Operativa 2013

Suggested Citation

  • Liliana Forzani & Ricardo Fraiman & Pamela Llop, 2013. "Density estimation for spatial-temporal models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 321-342, June.
    • Handle: RePEc:spr:testjl:v:22:y:2013:i:2:p:321-342
    DOI: 10.1007/s11749-012-0313-3
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    References listed on IDEAS

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