Detail publikace

Statistical properties of the local linear estimator of conditional density

Originální název

Statistical properties of the local linear estimator of conditional density

Anglický název

Statistical properties of the local linear estimator of conditional density

Jazyk

en

Originální abstrakt

This contribution focuses on the kernel conditional density estimations. % which provides a very comprehensive information about the analyzed data set. There are two basic estimators - the Nadaraya-Watson and the local linear estimator, we deal with the statistical properties of the second one. Derived characteristics of bias and variance of the estimator are compared with the results of the other authors via simulation study. The simulation study proved better statistical properties of the suggested characteristics. Additionally, the optimal values of smoothing parameters are derived by minimizing of Asymptotic Mean Integrated Squared Error. A data-driven method for practical estimation of the smoothing parameters is suggested - the derivation of formulas for the cross-validation method is extended from the Nadaraya-Watson to the local linear estimator.

Anglický abstrakt

This contribution focuses on the kernel conditional density estimations. % which provides a very comprehensive information about the analyzed data set. There are two basic estimators - the Nadaraya-Watson and the local linear estimator, we deal with the statistical properties of the second one. Derived characteristics of bias and variance of the estimator are compared with the results of the other authors via simulation study. The simulation study proved better statistical properties of the suggested characteristics. Additionally, the optimal values of smoothing parameters are derived by minimizing of Asymptotic Mean Integrated Squared Error. A data-driven method for practical estimation of the smoothing parameters is suggested - the derivation of formulas for the cross-validation method is extended from the Nadaraya-Watson to the local linear estimator.

Dokumenty

BibTex


@inproceedings{BUT137455,
  author="Kateřina {Pokorová}",
  title="Statistical properties of the local linear estimator of conditional density",
  annote="This contribution focuses on the kernel conditional density estimations. % which provides a very comprehensive information about the analyzed data set.
There are two basic estimators - the Nadaraya-Watson and the local linear estimator, we deal with the statistical properties of the second one. Derived characteristics of bias and variance of the estimator are compared with the results of the other authors via simulation study. The simulation study proved better statistical properties of the suggested characteristics.
Additionally, the optimal values of smoothing parameters are derived by minimizing of Asymptotic Mean Integrated Squared Error. A data-driven method for practical estimation of the smoothing parameters is suggested - the derivation of formulas for the cross-validation method is extended from the Nadaraya-Watson to the local linear estimator.
",
  booktitle="Matematika, informační technologie a aplikované vědy, MITAV 2017",
  chapter="137455",
  howpublished="electronic, physical medium",
  year="2017",
  month="june",
  pages="1--7",
  type="conference paper"
}