caa a22 4500 477072925 CHVBK 20180405111431.0 cr unu---uuuuu 170330e19960901xx s 000 0 eng 10.1007/BF01414875 doi (NATIONALLICENCE)springer-10.1007/BF01414875 Probability density estimation using a Gaussian clustering algorithm [Elektronische Daten] [J. Ćwik, J. Koronacki] A version of the Tråvén's [1] Gaussian clustering algorithm for normal mixture densities is studied. Unlike in the case of the Tråvén's algorithm, no constraints on covariance structure of mixture components are imposed. Simulations suggest that the modified algorithm is a very promising method of estimating arbitrary continuous d-dimensional densities. In particular, the simulations have shown that the algorithm is robust against assuming the initial number of mixture components to be too large. Springer-Verlag London Limited, 1996 Gaussian clustering neural network nationallicence Non-parametric density estimation nationallicence Ćwik J. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland aut Koronacki J. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland aut Neural Computing & Applications Springer-Verlag 4/3(1996-09-01), 149-160 0941-0643 4:3<149 1996 4 521 https://doi.org/10.1007/BF01414875 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01414875 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ćwik J. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland aut NATIONALLICENCE 700 1- Koronacki J. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland aut NATIONALLICENCE 773 0- Neural Computing & Applications Springer-Verlag 4/3(1996-09-01), 149-160 0941-0643 4:3<149 1996 4 521 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer