Best- and worst-case variances when bounds are available for the distribution function.

DOI10.1016/S0167-9473(98)00051-6zbMath1042.62508MaRDI QIDQ1274572

David S. Rubin, George S. Fishman

Publication date: 12 January 1999

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Mathematics Subject Classification ID

Exact distribution theory in statistics (62E15)

Related Items (1)

Worst-case estimation for econometric models with unobservable components

Cites Work

• Bounding the variance in Monte Carlo experiments
• Ranges of posterior probability over a distribution band
• The Complexity of Counting Cuts and of Computing the Probability that a Graph is Connected
• Evaluating Best-Case and Worst-Case Coefficients of Variation when Bounds Are Available
• Evaluating Best-Case and Worst-Case Variances When Bounds are Available
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