Accession Number:

ADA278799

Title:

Cramer-Von Mises Variance Estimators for Simulations

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF ADMINISTRATIVE SCIENCES

Report Date:

1993-09-01

Abstract:

We study estimators for the variance parameter sigma2 of a stationary process. The estimators are based on weightings yield estimators that are first-order unbiased for sigma 2 We derive an expression for the asymptotic variance of the new estimators this expression is then used to obtain the first-order unbiased estimator having the smallest variance among fixed-degree polynomial weighting functions. Although our work is based on asymptotic theory, we present exact and empirical examples to demonstrate the new estimators small-sample robustness. Simulation, Stationary process, Variance estimation, Standardized time series, Cramer-von mises estimator.

Descriptive Note:

Technical rept.

Supplementary Note:

DOI: 10.21236/ADA278799

Pages:

0027

Subject Categories:

Modernization Areas:

Distribution Statement:

Approved for public release; distribution is unlimited. Document partially illegible.

File Size:

1.05MB