Properties of batch means from stationary ARMA time series
MetadataShow full item record
The batch means process arising from an arbitrary autoregressive moving-average (ARMA) process time series is derived. As side results, the variance and correlation structures of the batch means process as functions of the batch size and parameters of the original process are obtained. Except for the first-order ARMA process, for which a closed-form expression is obtained, the parameters of the batch-means process are determined numerically. Keywords: Monte Carlo method; Simulation. (Author)
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
NPS Report NumberNPS55-86-004
Showing items related by title, author, creator and subject.
McGahern, Robert E. (Monterey, California. Naval Postgraduate School, 2004-12);The ability to transition technology developments to operational systems is of great importance to the Department of the Navy (DoN). One way to achieve increased transitions is to operate more efficiently - more "like a ...
Goral, Frank Ivan (Monterey, California. Naval Postgraduate School, 1979-12);The process of acquiring major weapon systems is the largest, most complex and dollar consuming process in the Department of Defense. The cycle from concept to delivery may require five to ten years. Consequently, decision ...
Gaver, Donald Paul; Jacobs, Patricia A. (Monterey, California. Naval Postgraduate School, 1992-11); NPS-OR-93-004Estimation of mean square prediction error of wind components is required in the optimal interpolation (OI) process in numerical prediction of atmospheric variables. Previous work has suggested that statistical models with ...