Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Almut E.D. Veraart"'
Publikováno v:
Stochastic Processes and their Applications. 145:241-268
This article generalises the concept of realised covariation to Hilbert-space-valued stochastic processes. More precisely, based on high-frequency functional data, we construct an estimator of the trace-class operator-valued integrated volatility pro
Publikováno v:
Scandinavian Journal of Statistics. Sep2014, Vol. 41 Issue 3, p693-724. 32p.
Autor:
Veraart, Almut
Publikováno v:
AStA Advances in Statistical Analysis; Sep2011, Vol. 95 Issue 3, p253-291, 39p
Autor:
Veraart, Almut E. D.
Publikováno v:
Econometric Theory; Apr2010, Vol. 26 Issue 2, p331-368, 38p, 5 Charts, 1 Graph
Autor:
Victor M. Panaretos, Yoav Zemel
This open access book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation. Further to reviewing state-of-the-art aspects, it also
Autor:
Fred Espen Benth, Giulia Di Nunno
These Proceedings offer a selection of peer-reviewed research and survey papers by some of the foremost international researchers in the fields of finance, energy, stochastics and risk, who present their latest findings on topical problems. The paper
Autor:
Ciprian Tudor
This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process
This book provides analytic tools to describe local and global behavior of solutions to Itô-stochastic differential equations with non-degenerate Sobolev diffusion coefficients and locally integrable drift. Regularity theory of partial differential
Autor:
Zheng Gao, Stilian Stoev
This book provides a unified exposition of some fundamental theoretical problems in high-dimensional statistics. It specifically considers the canonical problems of detection and support estimation for sparse signals observed with noise. Novel phase