Biomedical subjects
Publications and source records attributed to K S Lii.
Harmonizable processes with spectral mass concentrated on a number of straight lines are considered. The asymptotic behavior of the bias and covariance of a number of spectral estimates is described. The results generalize those obtained for periodic and almost periodic processes.
Non-Gaussian stationary autoregressive moving average sequences are considered. Under conditions concerning smoothness and positivity of the density function of the independent random variables generating the sequence, asymptotically efficient methods for the estimation of unknown coefficients of the model are described. The main interest is in nonminimum-phase models.
The structure of non-Gaussian autoregressive schemes is described. Asymptotically efficient methods for the estimation of the coefficients of the models are described under appropriate conditions, some of which relate to smoothness and positivity of the density function f of the independent random variables generating the process. The principal interest is in nonminimum phase models.
We consider the problem of estimating the filter generating a non-Gaussian linear process and the deconvolution of that process when the spectral density of the process has zeros. Without using a minimum phase assumption we show that often if there are only finitely many zeros there are procedures to effect such an estimation and deconvolution.