Asymptotic inference for LSE in multivariate continuous regression models with long-memory random fields

摘要

This paper establishes the asymptotic behaviour for the covariance matrix and the limit distributions of the least squares estimators for a regression coefficients in a multivariate continuous regression models with long-memory Gaussian errors. The used method is based on the asymptotic analysis of orthogonal expansion of non-linear functionals of homogeneous and isotropic Gaussian random fields.