Gannaz, Irène

Multivariate processes with long-range memory properties can be encountered in many applications fields. Two fundamentals characteristics in such frameworks are the long-memory parameters and the correlation between time series. We consider multivariate linear processes, not necessarily Gaussian, presenting long-memory dependence. We show that the ...

Mezhennaya, Natalia M. Mikhailov, Vladimir G.
Published in
Discrete Mathematics and Applications

Formulas for distributions of number of ones (non-zeroes) in the cycle of the output sequence of generalized binary Pohl generator are obtained. Limit theorems for these distributions are derived in the case when the lengths of registers are coprime and tend to infinity, the contents of different registers are independent, but cell contents within ...

Timashev, Aleksandr N.
Published in
Discrete Mathematics and Applications

We consider a generalized scheme of allocation of n particles (elements) over unordered cells (components) under the condition that the number of particles in each cell belongs to a fixed finite set A of positive integers. A new asymptotic estimates for the total number In(A) of variants of allocations of n particles are obtained under some conditi...

Gardes, Laurent Girard, Stephane Stupfler, Gilles

The Conditional Tail Expectation is an indicator of tail behaviour that has recently gained traction in actuarial and financial applications. Contrary to the quantile or Value-at-Risk, it takes into account the frequency of a tail event together with the probabilistic behaviour of the variable of interest on this event. However, the asymptotic norm...

Brault, Vincent Keribin, Christine Mariadassou, Mahendra

Latent Block Model (LBM) is a model-based method to cluster simultaneously the d columns and n rows of a data matrix. Parameter estimation in LBM is a difficult and multifaceted problem. Although various estimation strategies have been proposed and are now well understood empirically, theoretical guarantees about their asymptotic behavior is rather...

Benelmadani, Djihad Benhenni, Karim Louhichi, Sana

The problem of estimating the regression function in a fixed design models with correlated observations is considered. Such observations are obtained from several experimental units, each of them forms a time series. Based on the trapezoidal rule, we propose a simple kernel estimator and we derive the asymptotic expression of its integrated mean sq...

Azaïs, Jean-Marc Bachoc, François Klein, Thierry Lagnoux, Agnès Nguyen, Thi Mong Ngoc

We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic approximations of the mean and variance of this estimator, together with asymptotic normality results, for a large class of...

Chauvet, Guillaume Le Gleut, Ronan

International audience

Feray, Valentin

In 2018, Kahle and Stump raised the following problem: identify sequences of finite Coxeter groups Wn for which the two-sided descent statistics on a uniform random element of Wn is asymptotically normal. Recently, Brück and Röttger provided an almost-complete answer, assuming some regularity condition on the sequence Wn. In this note, we provide a...

Gardes, Laurent Guillou, Armelle Roman, Claire

We consider the estimation of an extreme conditional quantile. In a first part, we propose a new tail condition in order to establish the asymptotic distribution of an extreme conditional quantile estimator. Next, a general class of estimators is introduced, which encompasses, among others, kernel's or nearest neighbors' types of estimators. A unif...