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  • Multivariate kernel density estimators have become a common tool for empirical studies. These estimators depend on the choice of a crucial parameter -- the bandwidth matrix. In this paper, we propose an extension of the iterative method for finding the bandwidth matrix not only for density estimation but also for estimating its derivatives. This procedure is illustrated by a simulation study and two real data sets.
  • Multivariate kernel density estimators have become a common tool for empirical studies. These estimators depend on the choice of a crucial parameter -- the bandwidth matrix. In this paper, we propose an extension of the iterative method for finding the bandwidth matrix not only for density estimation but also for estimating its derivatives. This procedure is illustrated by a simulation study and two real data sets. (en)
Title
  • Bandwidth matrix selectors for multivariate kernel density estimation
  • Bandwidth matrix selectors for multivariate kernel density estimation (en)
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  • Bandwidth matrix selectors for multivariate kernel density estimation
  • Bandwidth matrix selectors for multivariate kernel density estimation (en)
skos:notation
  • RIV/00216224:14310/14:00074755!RIV15-MSM-14310___
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  • 4827
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  • RIV/00216224:14310/14:00074755
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  • kernel density estimation; iterative method; integrated square error (en)
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  • [7D02976ACCB5]
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  • Theoretical and Applied Issues in Statistics and Demography
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  • Koláček, Jan
  • Horová, Ivanka
  • Hasilová, Kamila
number of pages
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  • International Society for the Advancement of Science and Technology (ISAST)
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  • 9786188125773
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  • 14310
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