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Davide Giraudo

Publications and source records attributed to Davide Giraudo.

31 records · Page 2Linked to original sources
arXiv2019

An exponential inequality for $U$-statistics of i.i.d. data

We establish an exponential inequality for degenerated $U$-statistics of order $r$ of i.i.d. data. This inequality gives a control of the tail of the maxima absolute values of the $U$-statistic by the sum of two terms: an exponential term and one involving the tail of $h\left(X_1,\dots,X_r\right)$. We also give a version for not necessarily degenerated $U$-statistics having a symmetric kernel and furnish an application to the convergence rates in the Marcinkiewicz law of large numbers. Application to invariance principle in Hölder spaces is also considered.

math.PR↗
arXiv2019

Large deviation inequalities for martingales in Banach spaces

Let $(X_i, \mathcal{F}_i)_{i\geq1}$ be a martingale difference sequence in a smooth Banach space. Let $S_n=\sum_{i=1}^nX_i, n\geq 1,$ be the partial sums of $(X_i, \mathcal{F}_i)_{i\geq 1}$. We give upper bounds on the quantity $\mathbb{P}\left(\max_{1\leq k\leq n}\lVert S_k\rVert>nx\right)$ in terms of $ n\geq 1$ and $x>0$ in two different situations: when the martingale differences have uniformly bounded exponential moments and when the decay of the tail of the increments is polynomial.

math.PR↗
arXiv2018

Invariance principle via orthomartingale approximation

We obtain a necessary and sufficient condition for the orthomartingale-coboundary decomposition. We establish a sufficient condition for the approximation of the partial sums of a strictly stationary random fields by those of stationary orthomartingale differences. This condition can be checked under multidimensional analogues of the Hannan condition and the Maxwell-Woodroofe condition.

math.PR↗
arXiv2015

Holderian weak invariance principle under a Hannan type condition

We investigate the invariance principle in H{ö}lder spaces for strictly stationary martingale difference sequences. In particular, we show that the sufficient condition on the tail in the i.i.d. case does not extend to stationary ergodic martingale differences. We provide a sufficient condition on the conditional variance which guarantee the invariance principle in H{ö}lder spaces. We then deduce a condition in the spirit of Hannan one.

math.PR↗
arXiv2015

Integrability conditions on coboundary and transfer function for limit theorems

For a measure preserving automorphism $T$ of a probability space, we provide conditions on the tail function of $g\colonΩ\to\mathbb R$ and $g-g\circ T$ which guarantee limit theorems among the weak invariance principle, Marcinkievicz-Zygmund strong law of large numbers and the law of iterated logarithm to hold for $f:=m+g-g\circ T$, where $(m\circ T^i)\_{i\geqslant 0}$ is a martingale differences sequence.

math.PR↗
arXiv2015

Holderian weak invariance principle for stationary mixing sequences

We provide some sufficient mixing conditions on a strictly stationary sequence in order to guarantee the weak invariance principle in Hölder spaces. Strong mixing and $ρ$-mixing conditions are investigated as well as $τ$-dependent sequences. The main tools are Fuk-Nagaev type inequalities for mixing sequences and a truncation argument.

math.PR↗
arXiv2014

Orthomartingale-coboundary decomposition for stationary random fields

We provide a new projective condition for a stationary real random field indexed by the lattice $\Z^d$ to be well approximated by an orthomartingale in the sense of Cairoli (1969). Ourmain result can be viewed as a multidimensional version of the martingale-coboundary decomposition method which the idea goes back to Gordin (1969). It is a powerfull tool for proving limit theorems or large deviations inequalities for stationary random fields when the corresponding result is valid for orthomartingales.

math.PR↗
arXiv2014

A strictly stationary $β$-mixing process satisfying the central limit theorem but not the weak invariance principle

In 1983, N. Herrndorf proved that for a $ϕ$-mixing sequence satisfying the central limit theorem and $\liminf_{n\to\infty}\frac{σ^2_n}n>0$, the weak invariance principle takes place. The question whether for strictly stationary sequences with finite second moments and a weaker type ($α$, $β$, $ρ$) of mixing the central limit theorem implies the weak invariance principle remained open. We construct a strictly stationary $β$-mixing sequence with finite moments of any order and linear variance for which the central limit theorem takes place but not the weak invariance principle.

math.PR↗