Asymptotics For Statistical Distances Based On Voronoi Tessellations

Below is result for Asymptotics For Statistical Distances Based On Voronoi Tessellations in PDF format. You can download or read online all document for free, but please respect copyrighted ebooks. This site does not host PDF files, all document are the property of their respective owners.

processes - jstor.org

Dereich, S., Mönch, C. and Mörters, P. Typical distances in ultrasmall random networks De Saporta, B. see Brandejsky, A. Doumas, A. V. and Papanicolaou, V. G. The coupon collector's problem revisited: asymptoticsof the variance Dufour, F., Horiguchi, M. and Piunovskiy, A. B. The expected total cost criterion for Markov

Resumen curricular: Raul Jim enez

Asymptotics for statistical distances based on Voronoi tessellations. J. Theoretical Probab. 15, 503{41.

MR2458183 (2010c:94013) 94A15 (62G20) (4-CARD-SM); (F

Asymptotics for statistical distances based on Voronoi tessellations. J. Theoret. Probab. 15 503 541. MR1898817 MR1898817 (2003d:60068) 20. KAPUR, J. N. (1989). Maximum-Entropy Models in Science and Engineering. Wiley, New York. MR1079544 MR1079544 (92b:00017) 21. KOZACHENKO, L. and LEONENKO, N. (1987). On statistical estimation of entropy of a random vector.

QUADRATURE ERRORS, DISCREPANCIES AND THEIR RELATIONS

point distribution methods it is based on weighted centroidal Voronoi tessellations and Lloyd s iterative algorithm [26, 40]. Recall that Lloyd s algorithm tries to nd a useful minimizer of the error functional L((p k;V k)M =1) := XM k=1 Z V k w(x)jx p kj2 dx over any set of points fp kgM k=1 belonging to ˆR2 and any tessellation fV kg M k=1 of. A necessary