Add to ORKGAbstract: Kernel type density estimators are studied for random fields. A functional central limit theorem in the space of square integrable functions is proved if the locations of observations become more and more dense in an increasing sequence of domains. Zusammenfassung: Es werden Kerndichteschätzer für stochastische Felder untersucht. Ein funktionaler Grenzwertsatz im Raum der quadratisch inte-grierbaren Funktionen wird bewiesen für den Fall, dass die Lokationen der Beobachtungen immer dichter werden in einer wachsenden Folge von Be-reichen
Abstract: We establish a representation as a sum of independent random variables, plus a remainder t...
Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimen...
In the present work we investigate kernel-type estimators for product densities and for the pair cor...
Abstract: Kernel type density estimators are studied for random fields. A functional central limit t...
Kernel type density estimators are studied for random fields. A functional central limit theorem in ...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
The Central Limit Theorem is considered for m-dependent random fields. The random field is observed i...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
Abstract: We establish a representation as a sum of independent random variables, plus a remainder t...
Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimen...
In the present work we investigate kernel-type estimators for product densities and for the pair cor...
Abstract: Kernel type density estimators are studied for random fields. A functional central limit t...
Kernel type density estimators are studied for random fields. A functional central limit theorem in ...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
The Central Limit Theorem is considered for m-dependent random fields. The random field is observed i...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
Abstract: We establish a representation as a sum of independent random variables, plus a remainder t...
Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimen...
In the present work we investigate kernel-type estimators for product densities and for the pair cor...