This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical random fields, in the high-frequency limit. The sequences of fields that we consider are represented as smoothed averages of spherical Gaussian eigenfunctions and can be viewed as random coefficients from continuous wavelets/needlets; as such, they are of immediate interest for spherical data analysis. In particular, we focus on so-called needlets polyspectra, which are popular tools for non-Gaussianity analysis in the astrophysical community, and on the area of excursion sets. Our results are based on Stein-Malliavin approximations for nonlinear transforms of Gaussian fields, and on an explicit derivation on the high-frequency limit of their varia...
International audienceThe angular power spectrum of a stationary random field on the sphere is estim...
In a recent paper, we analyzed the properties of a new kind of spherical wavelets (called needlets) ...
We study the asymptotic behaviour of needlets-based approximate maximum likelihood estimators for th...
This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical random...
This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical rando...
This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical random...
We investigate invariant random fields on the sphere using a new type of spherical wavelets, called ...
We investigate here a generalized construction of spherical wavelets/needlets which admits extra-fle...
35 pages with 2 figuresThe main point of this paper is the investigation of invariant random fields ...
This thesis is a collection of essays on spherical wavelets and their applications on statistical mo...
We show how it is possible to assess the rate of convergence in the Gaussian approximation of triang...
We establish here a quantitative central limit theorem (in Wasserstein distance) for the Euler–Poinc...
In recent years, considerable interest has been drawn by the analysis of geometric functionals for t...
In a recent paper, we analyzed the properties of a new kind of spherical wavelets (called needlets) ...
We compute explicit upper bounds on the distance between the law of a multivariate Gaussian distribu...
International audienceThe angular power spectrum of a stationary random field on the sphere is estim...
In a recent paper, we analyzed the properties of a new kind of spherical wavelets (called needlets) ...
We study the asymptotic behaviour of needlets-based approximate maximum likelihood estimators for th...
This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical random...
This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical rando...
This paper provides quantitative Central Limit Theorems for nonlinear transforms of spherical random...
We investigate invariant random fields on the sphere using a new type of spherical wavelets, called ...
We investigate here a generalized construction of spherical wavelets/needlets which admits extra-fle...
35 pages with 2 figuresThe main point of this paper is the investigation of invariant random fields ...
This thesis is a collection of essays on spherical wavelets and their applications on statistical mo...
We show how it is possible to assess the rate of convergence in the Gaussian approximation of triang...
We establish here a quantitative central limit theorem (in Wasserstein distance) for the Euler–Poinc...
In recent years, considerable interest has been drawn by the analysis of geometric functionals for t...
In a recent paper, we analyzed the properties of a new kind of spherical wavelets (called needlets) ...
We compute explicit upper bounds on the distance between the law of a multivariate Gaussian distribu...
International audienceThe angular power spectrum of a stationary random field on the sphere is estim...
In a recent paper, we analyzed the properties of a new kind of spherical wavelets (called needlets) ...
We study the asymptotic behaviour of needlets-based approximate maximum likelihood estimators for th...