Central limit theorem for Gibbsian U-statistics of facet processes

Jakub Večeřa

Applications of Mathematics (2016)

  • Volume: 61, Issue: 4, page 423-441
  • ISSN: 0862-7940

Abstract

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A special case of a Gibbsian facet process on a fixed window with a discrete orientation distribution and with increasing intensity of the underlying Poisson process is studied. All asymptotic joint moments for interaction U-statistics are calculated and the central limit theorem is derived using the method of moments.

How to cite

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Večeřa, Jakub. "Central limit theorem for Gibbsian U-statistics of facet processes." Applications of Mathematics 61.4 (2016): 423-441. <http://eudml.org/doc/283401>.

@article{Večeřa2016,
abstract = {A special case of a Gibbsian facet process on a fixed window with a discrete orientation distribution and with increasing intensity of the underlying Poisson process is studied. All asymptotic joint moments for interaction U-statistics are calculated and the central limit theorem is derived using the method of moments.},
author = {Večeřa, Jakub},
journal = {Applications of Mathematics},
keywords = {central limit theorem; facet process; U-statistics; central limit theorem; facet process; U-statistics},
language = {eng},
number = {4},
pages = {423-441},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Central limit theorem for Gibbsian U-statistics of facet processes},
url = {http://eudml.org/doc/283401},
volume = {61},
year = {2016},
}

TY - JOUR
AU - Večeřa, Jakub
TI - Central limit theorem for Gibbsian U-statistics of facet processes
JO - Applications of Mathematics
PY - 2016
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 61
IS - 4
SP - 423
EP - 441
AB - A special case of a Gibbsian facet process on a fixed window with a discrete orientation distribution and with increasing intensity of the underlying Poisson process is studied. All asymptotic joint moments for interaction U-statistics are calculated and the central limit theorem is derived using the method of moments.
LA - eng
KW - central limit theorem; facet process; U-statistics; central limit theorem; facet process; U-statistics
UR - http://eudml.org/doc/283401
ER -

References

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  6. Peccati, G., Taqqu, M. S., Wiener chaos: Moments, Cumulants and Diagrams. A survey with computer implementation, Bocconi University Press, Milano; Springer, Milan (2011). (2011) Zbl1231.60003MR2791919
  7. Reitzner, M., Schulte, M., 10.1214/12-AOP817, Ann. Probab. 41 (2013), 3879-3909. (2013) Zbl1293.60061MR3161465DOI10.1214/12-AOP817
  8. Schreiber, T., Yukich, J. E., 10.1214/12-AIHP500, Ann. Inst. Henri Poincaré, Probab. Stat. 49 (2013), 1158-1182. (2013) Zbl1308.60064MR3127918DOI10.1214/12-AIHP500
  9. Večeřa, J., Beneš, V., 10.1007/s11009-016-9485-8, Methodol. Comput. Appl. Probab. DOI-10.1007/s11009-016-9485-8 (2016). (2016) Zbl1370.60015MR3564860DOI10.1007/s11009-016-9485-8

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