Hyperbolic wavelet thresholding methods and the curse of dimensionality through the maxiset approach

In this paper we compute the maxisets of some denoising methods (estimators) for multidimensional signals based on thresholding coefficients in hyperbolic wavelet bases. That is, we determine the largest functional space over which the risk of these estimators converges at a chosen rate. In the unidimensional setting, refining the choice of the coefficients that are subject to thresholding by pooling information from geometric structures in the coefficient domain (e.g., vertical blocks) is known to provide ‘large maxisets’. In the multidimensional setting, the situation is less straightforward. In a sense these estimators are much more exposed to the curse of dimensionality. However we identify cases where information pooling has a clear benefit. In particular, we identify some general structural constraints that can be related to compound functional models and to a minimal level of anisotropy.     

A General Darling–Erdős Theorem in Euclidean Space

We provide an improved version of the Darling–Erd?s theorem for sums of i.i.d. random variables with mean zero and finite variance. We extend this result to multidimensional random vectors. Our proof is based on a new strong invariance principle in this setting which has other applications as well such as an integral test refinement of the multidimensional Hartman–Wintner LIL. We also identify a borderline situation where one has weak convergence to a shifted version of the standard limiting distribution in the classical Darling–Erd?s theorem.     

Stability of Maxima of Random Variables with Multidimensional Indices

The paper discusses the stability of suitably-defined maxima of a set of i.i.d. random variables with multidimensional indices.It is shown that theorems of Gnedenko (1943) and Tomkins (1986) concerning relative stability and complete relative stability of maxima remain valid in the new setting.Moreover, a criterion for almost sure relative stability for maxima with multidimensional indices is presented, extending a result of Barndorff-Nielsen (1963).AMS 2000 Subject Classification. Primary—60F15, 60G60, 62G30, Secondary—10A25, 60G99     

Multidimensional Toeplitz operators with locally sectorial symbols

We study a class of Toeplitz operators with discontinuous symbols, stimulated by classical work of Douglas and Widom. We extend the notion of a locally sectorial symbol from the setting of scalar Toeplitz operators on the circle to systems, acting on sections of vector bundles over a class of multidimensional domains with minimal smoothness, known as uniformly rectifiable domains, and establish Fredholm properties in this expanded setting.     

A concept of absolute continuity and its characterization in terms of convergence in variation

We study the notion of φ‐absolute continuity, providing several equivalent definitions, and we prove a characterization of the space of φ‐absolutely continuous functions in terms of convergence in variation for a family of Mellin integral operators in the multidimensional setting.     

Nonlinear estimation in anisotropic multi-index denoising

In the framework of denoising a function depending of a multidimensional variable (for instance an image), we provide a nonparametric procedure which constructs a pointwise kernel estimation with a local selection of the multidimensional bandwidth parameter. Our method is a generalization of the Lepski's method of adaptation, and roughly consists in choosing the “coarsest” bandwidth such that the estimated bias is negligible. However, this notion becomes more delicate in a multidimensional setting. We will particularly focus on functions with inhomogeneous smoothness properties and especially providing a possible disparity of the inhomogeneous aspect in the different directions. We show, in particular that our method is able to exactly attain the minimax rate or to adapt to unknown degree of anisotropic smoothness up to a logarithmic factor, for a large scale of anisotropic Besov spaces. Received: 11 November 1999 / Revised version: 14 November 2000 / Published online: 24 July 2001     

Approximation in variation for Mellin integral operators

We study approximation results for a family of Mellin integral operators in the space of functions of bounded variation in the multidimensional setting, by means of a new concept of variation for multivariate functions. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Bivariate Hermite-Birkhoff interpolation and Vandermonde determinants

The concepts of Vandermonde determinant and confluent Vandermonde determinant are extended to the multidimensional setting by relating them to multivariate interpolation problems. With an approach different from that of other recent papers on this subject, the values of these determinants are computed, recovering and extending the results of those papers.Partially supported by Research Grant PS900121 DGICYT.     

Localization of periodic orbits of polynomial systems by ellipsoidal estimates

In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb’s equations for a three-mode operating cavity in a laser are considered.     

Rearrangement transformations on general measure spaces

For a general set transformation R between two measure spaces, we define the rearrangement of a measurable function by means of the Layer's cake formula. We study some functional properties of the Lorentz spaces defined in terms of R, giving a unified approach to the classical rearrangement, Steiner's symmetrization, the multidimensional case, and the discrete setting of trees.     

Dependence structure of sojourn times via partition separated ordering

We investigate the joint distribution of successive sojourn times of a customer traversing a path in a Jackson network. It is shown in a general setting that sojourn times for a broad class of such paths exhibit positive dependence. This applies to paths which admit overtaking due to the network topology as well as due to the internal node structure. Our proofs utilize the concept of partition separated orders on multidimensional ordered spaces.     

The Fixed Point Problem for Systems of Coordinate-Wise Uniformly Monotone Operators and Applications

We study the fixed point problem for a system of multivariate operators that are coordinate-wise uniformly monotone, in the setting of quasi-ordered sets. We show that this problem is equivalent to the fixed point problem for a mixed monotone operator that can be explicitly constructed. As a consequence, we obtain a criterion for the existence and uniqueness of solution to the considered problem, together with an approximating iterative scheme, in the setting of partially ordered metric spaces. As an application, we investigate a new abstract multidimensional fixed point problem. To validate our results, we also provide an application to a first-order differential system with periodic boundary value conditions.     

Convexity bounds for BSDE solutions, with applications to indifference valuation

We consider backward stochastic differential equations (BSDEs) with a particular quadratic generator and study the behaviour of their solutions when the probability measure is changed, the filtration is shrunk, or the underlying probability space is transformed. Our main results are upper bounds for the solutions of the original BSDEs in terms of solutions to other BSDEs which are easier to solve. We illustrate our results by applying them to exponential utility indifference valuation in a multidimensional It? process setting.     

Recovery of a Rapidly Oscillating Absolute Term in the Multidimensional Hyperbolic Equation

The paper is devoted to the development of the theory of inverse problems for evolution equations with summands rapidly oscillating in time. A new approach to setting such problems is developed for the case in which additional constraints (overdetermination conditions) are imposed only on several first terms of the asymptotics of the solution rather that on the whole solution. This approach is realized in the case of a multidimensional hyperbolic equation with unknown absolute term.     

Optimal rebalancing frequencies for multidimensional portfolios

We study optimal investment with multiple assets in the presence of small proportional transaction costs. Rather than computing an asymptotically optimal no-trade region, we optimize over suitable trading frequencies. We derive explicit formulas for these and the associated welfare losses due to small transaction costs in a general, multidimensional diffusion setting, and compare their performance to a number of alternatives using Monte Carlo simulations.     

Higher order Riesz transforms,fractional derivatives,and Sobolev spaces for Laguerre expansions

We study different Sobolev spaces associated with multidimensional Laguerre expansions. To do this we establish an analogue of P.A. Meyer's multiplier theorem, prove some transference results between higher order Riesz–Hermite and Riesz–Laguerre transforms, and introduce fractional derivatives and integrals corresponding to the Laguerre setting. Hypercontractivity of the Laguerre semigroups and Calderón's reproduction formula are also discussed.     

Algorithms for fast multidimensional signal extraction

In recent studies operator factorization techniques have been developed for problems associated with multidimensional control and image processing. In particular the “special factorization” of Gohberg and Krein and the Schur-Coleski factorization have both been extended to the multivariate setting. The present study focuses on computational aspects of the earlier results. Also of interest are implications for designing computer architectures which facilitate high-speed, online computation of the operator factors.     

Multivariate θ-generalized normal distributions

A new family of continuous multivariate distributions is introduced, generalizing the canonical form of the multivariate normal distribution. The well-known univariate version of this family, as developed by Box, Tiao and Lund, among others, has proven a valuable tool in Bayesian analysis and robustness studies, as well as serving as a unified model for least θ's and maximum likelihood estimates. The purpose of the family introduced here is to extend, to a degree of generality which will permit practical applications, the useful role played by the univariate family to a multidimensional setting.     

Berry–Esseen bounds in the inhomogeneous Curie–Weiss model with external field

We study the inhomogeneous Curie–Weiss model with external field, where the inhomogeneity is introduced by adding a positive weight to every vertex and letting the interaction strength between two vertices be proportional to the product of their weights. In this model, the sum of the spins obeys a central limit theorem outside the critical line. We derive a Berry–Esseen rate of convergence for this limit theorem using Stein’s method for exchangeable pairs. For this, we, amongst others, need to generalize this method to a multidimensional setting with unbounded random variables.     

Renormalisation du produit, Jacobiens et transformations de Riesz

The “correction algorithm”, applied in probability theory to the pointwise product of two martingales, has a natural analogue in the real-variable setting. It turns out that the corresponding bilinear operators obtained in this way provide us with a new “renormalization algorithm”, in the sense of Coifman, Dobyinski and Meyer. We give a few examples of applications, regarding multidimensional Hardy spaces and various nonlinear quantities.