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.
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