Normal approximation for quasi associated random fields

• Keywords and Phrases: Spherical Random Fields, High-Frequency Gaussianity, High- Frequency Ergodicity, Gaussian Subordination, Clebsch-Gordan Coefficients, Cosmic Variance.. •

In Section 3, we focus on the stationary case and establish strong connections between asymptotic properties of C(0) and properties of the max-stable random field η such as

Key words and phrases: Central limit theorem, spatial processes, m-dependent random fields, physical dependence measure, nonparametric estimation, kernel density estimator, rate

Let us now consider some numerical illustrations on the examples we have given, in order to compare our extremal predictors with the Expectile Regression Predictor and the

We shall first define a very general class, noted as D, of quadratic models in terms of the power spectrum of the underlying Gaussian field, and then we shall show that the two

The aim of this paper is to establish multidimensional normal approximation results for vectors of random variables hav- ing the form of wavelet coefficients integrated with respect

The aim of this paper is to establish multidimensional normal approximation results for vectors of random variables having the form of wavelet coefficients integrated with respect to

Our aim is to discuss advantages of quasi-random points (also known as uniformly distributed (UD) points [8]) and their sub-class recently proposed by the authors [17] that