Buch
Nonparametric Kernel Density Estimation and Its Computational Aspects
Artur Gramacki
149,79
EUR
Lieferzeit 12-13 Tage
Übersicht
Verlag | : | Springer International Publishing |
Buchreihe | : | Studies in Big Data (Bd. 37) |
Sprache | : | Englisch |
Erschienen | : | 04. 06. 2019 |
Seiten | : | 176 |
Einband | : | Kartoniert |
Höhe | : | 235 mm |
Breite | : | 155 mm |
Gewicht | : | 326 g |
ISBN | : | 9783319890944 |
Sprache | : | Englisch |
Autorinformation
Artur Gramacki is an assistant professor at the Institute of Control and Computation Engineering of the University of Zielona Góra, Poland. His main interests cover general exploratory data analysis, while recently he has focused on parametric and nonparametric statistics as well as kernel density estimation, especially its computational aspects. In his career, he has also been involved in many projects related to the design and implementation of commercial database systems, mainly using Oracle RDBMS. He is a keen supporter of the R Project for Statistical Computing, which he tries to use both in his research and teaching activities.    
Inhaltsverzeichnis
Introduction.- Nonparametric density estimation.- Kernel density estimation .- Bandwidth selectors for kernel density estimation.- FFT-based algorithms for kernel density estimation and band-width selection.- FPGA-based implementation of a bandwidth selection algorithm.- Selected applications related to kernel density estimation.- Conclusion and further research.