The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as weak consistency ...
Motivated by global analysis of aircraft-based measurements of air pollutants and climate variables, and specifically the COVID-19 pandemic’s possible impact on ozone concentrations, a functional autoregressive model is proposed to capture global spatio-te ...
In this paper, we introduce the concept of isotropic Hilbert -valued spherical random field, thus extending the notion of isotropic spherical random field to an infinite -dimensional setting. We then establish a spectral representation theorem and a functi ...
We consider the problem of estimating the autocorrelation operator of an autoregressive Hilbertian process. By means of a Tikhonov approach, we establish a general result that yields the convergence rate of the estimated autocorrelation operator as a funct ...
We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an identically distribute ...
In this paper, we focus on isotropic and stationary sphere-cross-time random fields. We first introduce the class of spherical functional autoregressive-moving average processes (SPHARMA), which extend in a natural way the spherical functional autoregressi ...
