Density estimate and its application to analysis of temperature series

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Authors

HOROVÁ Ivanka ZELINKA Jiří BRÁZDIL Rudolf BUDÍKOVÁ Marie

Year of publication 2003
Type Article in Periodical
Magazine / Source Environmetrics
MU Faculty or unit

Faculty of Science

Citation
Web Odkaz na text článku na internetových stránkách časopisu Environmetrics
Field General mathematics
Keywords kernel estimate; visualization; air temperature; Prague-Klementinum; Central England
Description Nonparametric density estimates attempt to reconstruct the probability density from which a random sample has come, using the sample values and as few assumptions as possible about the density. These methods are smoothing operations on the sample distribution. Methods of kernel estimates represent one of the most effective nonparametric methods. These methods are simple to understand, easy to implement and they have very good mathematical properties. We employed the automatic procedure for the selection of the bandwidth, the kernel and the order of the kernel. This procedure is used for analysis of air temperature fluctuations for series of Central England and Prague-Klementinum in the periods 1661-2000 and 1771-2000, respectively. Graphical representation of the family of estimated densities in three dimensional space provide a better explanation of the long-term trends in temperature distribution of both series.
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