On least squares discrete Fourier analysis of unequally spaced data
Tom 47 / 2020
Streszczenie
The problem of discrete Fourier analysis of observations at non-equidistant times using the standard set of complex harmonics , t\in \mathbb {R}, k=0,\pm 1,\pm 2,\ldots , and the least squares method is studied. The observation model y_j = f(t_j) + \eta _j, j=1,\ldots ,n, is considered for f\in L^2[0,1], where t_j\in [(j-1)/n,j/n), and \eta _j are correlated complex valued random variables with E_\eta \eta _j=0 and E_\eta |\eta _j|^2=\sigma _\eta ^2 \lt \infty . Uniqueness and finite sample properties of the observed function Fourier coefficient estimators \hat c_k, k=0,\pm 1,\ldots ,\pm m, where m \lt n/(8\pi ), obtained by the least squares method, as well as of the corresponding orthogonal projection estimator \hat f_N(t)=\sum _{k=-m}^m\hat c_k\exp (i2\pi kt), where N=2m+1, are examined and compared with those of the standard Discrete Fourier Transform.