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 and asymptotic normality.
Caponera, A., Durastanti, C. (2022). Parametric estimation for functional autoregressive processes on the sphere. THEORY OF PROBABILITY AND MATHEMATICAL STATISTICS, 106(0), 63-83 [10.1090/tpms/1165].
Parametric estimation for functional autoregressive processes on the sphere
Caponera, A;
2022
Abstract
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 and asymptotic normality.File in questo prodotto:
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