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Estimating the Variance

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Statistical Decision Theory

Part of the book series: SpringerBriefs in Statistics ((BRIEFSSTATIST))

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Abstract

This chapter deals with estimation of the variance of a normal distribution.

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References

  • French, S., & Insua, D. R. (2004). Statistical decision theory. New York: Oxford University Press.

    Google Scholar 

  • Henderson, C. R. (1984a). Applications of linear models in animal breeding. Guelph: University of Guelph.

    Google Scholar 

  • Henderson, C. R. (1984b). ANOVA, MIVQUE, REML, and ML algorithms for estimation of variances and covariances. In H. A. David & H. T. David (Eds.), Statistics: An appraisal (pp. 257–280). Iowa State University.

    Google Scholar 

  • Koenker, R. (2005). Quantile regression. Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  • Le Cam, L. (1986). Asymptotic methods in statistical decision theory. New York: Springer-Verlag.

    Book  MATH  Google Scholar 

  • Liese, F., & Miescke, K. J. (2008). Statistical decision theory. Estimation, testing and selection. Springer-Verlag, New York.

    Google Scholar 

  • Longford, N. T. (2013). Assessment of precision with aversity to overstatement. South African Statistical Journal, 47, 49–59.

    MathSciNet  Google Scholar 

  • Markowitz, E. (1968). Minimum mean-square-error of estimation of the standard deviation of the normal distribution. The American Statistician, 22, 26.

    Google Scholar 

  • McCulloch, C. E., Searle, S. R., & Casella, G. (2006). Variance components (2nd ed.). New York: Wiley.

    MATH  Google Scholar 

  • Rapoport, A. (2010). Decision theory and decision behaviour. Dordrecht: Kluwer.

    Google Scholar 

  • Simon, M. K. (2004). Probability distributions involving Gaussian random variables. New York: Springer-Verlag.

    Google Scholar 

  • Stuart, A. (1969). Reduced mean-square-error estimation of \(\sigma ^p\) in normal samples. The American Statistician, 23, 27–28.

    Google Scholar 

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Correspondence to Nicholas T. Longford .

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Longford, N.T. (2013). Estimating the Variance. In: Statistical Decision Theory. SpringerBriefs in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40433-7_3

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