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The correlation between mean and variance estimators

Authors:

Keebom Kang,

David GoldsmanAuthors Info & Claims

WSC '85: Proceedings of the 17th conference on Winter simulation

Pages 211 - 216

https://doi.org/10.1145/21850.253155

Published: 15 December 1985 Publication History

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Abstract

One of the pitfalls encountered when using confidence interval estimators for the mean of a stationary stochastic process is that the mean and variance estimators (X and V) may be correlated. We derive Corr (X, V) for various variance estimators and stochastic processes, and we examine the effects of this correlation upon confidence interval estimator performance. Among the variance estimators under consideration are those arising from the methods of batched means and standardized time series. Both small sample and asymptotic results are reported.

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Laradji AJoarder A(2022)Alternative Ways for the Covariance Between Sample Mean and VarianceBulletin of the Malaysian Mathematical Sciences Society10.1007/s40840-022-01305-045:S1(315-324)Online publication date: 4-Aug-2022
https://doi.org/10.1007/s40840-022-01305-0
KANG KGOLDSMAN D(2007)The Correlation Between Mean and Variance Estimators in Computer SimulationIIE Transactions10.1080/0740817900896415322:1(15-23)Online publication date: 30-May-2007
https://doi.org/10.1080/07408179008964153
Goldsman D(1985)Ranking and selection procedures using standardized time seriesProceedings of the 17th conference on Winter simulation10.1145/21850.253094(120-124)Online publication date: 15-Dec-1985
https://dl.acm.org/doi/10.1145/21850.253094

The correlation between mean and variance estimators
1. Mathematics of computing

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WSC '85: Proceedings of the 17th conference on Winter simulation

December 1985

620 pages

ISBN:0911801073

DOI:10.1145/21850

Editors:
Donald T. Gantz
George Mason Univ., Fairfax, VA
,
Gerard C. Blais
Federal Computer Performance Evaluation and Simulation Center
,
Susan L. Solomon
California State Univ., Sacramento

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 December 1985

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Laradji AJoarder A(2022)Alternative Ways for the Covariance Between Sample Mean and VarianceBulletin of the Malaysian Mathematical Sciences Society10.1007/s40840-022-01305-045:S1(315-324)Online publication date: 4-Aug-2022
https://doi.org/10.1007/s40840-022-01305-0
KANG KGOLDSMAN D(2007)The Correlation Between Mean and Variance Estimators in Computer SimulationIIE Transactions10.1080/0740817900896415322:1(15-23)Online publication date: 30-May-2007
https://doi.org/10.1080/07408179008964153
Goldsman D(1985)Ranking and selection procedures using standardized time seriesProceedings of the 17th conference on Winter simulation10.1145/21850.253094(120-124)Online publication date: 15-Dec-1985
https://dl.acm.org/doi/10.1145/21850.253094

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Correlation among estimators of the variance of the sample mean

Mean likelihood estimators

Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): applications to tomography

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Correlation among estimators of the variance of the sample mean

Mean likelihood estimators

Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): applications to tomography

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