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14-18 August 2017
Uppsala University
Europe/Stockholm timezone

Methods for bandwidth detection in kernel conditional density estimations

15 Aug 2017, 13:30
Ångströmslaboratoriet (Uppsala University)


Uppsala University



Ms Katerina Konecna (Masaryk University)


This contribution is focused on the kernel conditional density estimations (KCDE). The estimation depends on the smoothing parameters which influence the final density estimation significantly. This is the reason why a requirement of any data-driven method is needed for bandwidth estimation. In this contribution, the cross-validation method, the iterative method and the maximum likelihood approach are conducted for bandwidth selection of the estimator. An application on a real data set is included and the proposed methods are compared.

Primary author

Ms Katerina Konecna (Masaryk University)

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