The asymptotic normality for the least squares estimator of parameters in a two dimensional sinusoidal model of observations
Copyright policy )The asymptotic normality for the least squares estimator of parameters in a two dimensional sinusoidal model of observations
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Brouwer's fixed-point theorem, asymptotic normality, least squares estimator, Random fields; image analysis, \( \mu \)-admissibility, Functional data analysis, asymptotic uniqueness, homogeneous and isotropic Gaussian random field, General nonlinear regression, reduction theorem, Inference from stochastic processes and spectral analysis, two-dimensional sinusoidal model, spectral measure of the regression function
Brouwer's fixed-point theorem, asymptotic normality, least squares estimator, Random fields; image analysis, \( \mu \)-admissibility, Functional data analysis, asymptotic uniqueness, homogeneous and isotropic Gaussian random field, General nonlinear regression, reduction theorem, Inference from stochastic processes and spectral analysis, two-dimensional sinusoidal model, spectral measure of the regression function
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