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Improved variance estimation under sub-space restriction

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  • Arashi, M.
  • Tabatabaey, S.M.M.

Abstract

For the linear regression model , we assume that for a given positive definite scale matrix , the error vector has a multivariate normal distribution and has the inverted Wishart distribution. For under an orthogonal sub-space restriction , we propose restricted unbiased, preliminary test and Stein-type estimators of variance of the error term, for when the scale of the inverse Wishart distribution is assumed to be unknown. We compare the weighted quadratic risks of the underlying estimators and propose dominance pictures for them.

Suggested Citation

  • Arashi, M. & Tabatabaey, S.M.M., 2009. "Improved variance estimation under sub-space restriction," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1752-1760, September.
  • Handle: RePEc:eee:jmvana:v:100:y:2009:i:8:p:1752-1760
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    References listed on IDEAS

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    1. Giles, Judith A., 1991. "Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances," Journal of Econometrics, Elsevier, vol. 50(3), pages 377-398, December.
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    4. Giles, Judith A., 1992. "Estimation of the error variance after a preliminary-test of homogeneity in a regression model with spherically symmetric disturbances," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 345-361.
    5. Ullah, Aman & Zinde-Walsh, Victoria, 1984. "On the Robustness of LM, LR, and W Tests in Regression Models," Econometrica, Econometric Society, vol. 52(4), pages 1055-1066, July.
    6. Arellano-Valle, Reinaldo B. & Bolfarine, Heleno, 1995. "On some characterizations of the t-distribution," Statistics & Probability Letters, Elsevier, vol. 25(1), pages 79-85, October.
    7. Arashi, M. & Tabatabaey, S.M.M., 2008. "Stein-type improvement under stochastic constraints: Use of multivariate Student-t model in regression," Statistics & Probability Letters, Elsevier, vol. 78(14), pages 2142-2153, October.
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    Cited by:

    1. Arashi, M. & Kibria, B.M. Golam & Norouzirad, M. & Nadarajah, S., 2014. "Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 53-74.
    2. Hu, Guikai & Yu, Shenghua & Luo, Han, 2015. "Comparisons of variance estimators in a misspecified linear model with elliptically contoured errors," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 266-276.
    3. A. Saleh & B. Kibria, 2013. "Improved ridge regression estimators for the logistic regression model," Computational Statistics, Springer, vol. 28(6), pages 2519-2558, December.
    4. Roozbeh, Mahdi, 2015. "Shrinkage ridge estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 56-74.
    5. M. Arashi & Mahdi Roozbeh, 2019. "Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data," Statistical Papers, Springer, vol. 60(3), pages 667-686, June.
    6. A. Saleh & B. Golam Kibria, 2011. "On some ridge regression estimators: a nonparametric approach," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 819-851.

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