Three types of estimator of the second spectral moment of a stationary Gaussian process are considered. The integral estimator is based on the integral of the squared derivative of the process, while crossing estimators make use of the number of upcrossings of zero or nonzero levels. It is shown that the zero-crossing estimator can often compete with the integral estimator in efficiency and that it can be considerably improved by the additional use of nonzero levels.
|Publication status||Published - 1974|
Subject classification (UKÄ)
- Probability Theory and Statistics
- Time-series estimation
- Stationary normal processes
- Spectral moments
- Level crossings