A new method of multiple imputation for completely (or almost completely) missing data
MACMESE'10 Proceedings of the 12th WSEAS international conference on Mathematical and computational methods in science and engineering
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Two alternative philosophical frameworks for the two problems of estimating the time-invariant or time-variant autocorrelation function and its Fourier transform for stationary and cyclostationary time-series are compared. One is based on the stochastic process model, and the other is based on the nonstochastic time-series model. It is then explained that results on estimator bias and variance for these two problems couched within the stochastic process framework have analogs within the nonstochastic framework. The bias and variance results for cyclostationary time-series that are available within these two frameworks are then summarized