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Statistical Decision Theory pp 1–15Cite as

Introduction

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Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Abstract

Most statisticians are accustomed to concluding the formal part of their analysis by one or several estimates.

Keywords

  • Loss Function
  • Unbiased Estimator
  • Inferential Statement
  • Sample Quantity
  • Complex Hypothesis

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-642-40433-7_1
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References

  • Berger, J. O. (1985). Statistical decision theory and bayesian analysis (2nd ed.). NewYork: Springer-Verlag.

    CrossRef  MATH  Google Scholar 

  • DeGroot, M. H. (2004). Optimal statistical decisions. New York: McGraw-Hill.

    CrossRef  MATH  Google Scholar 

  • Ferguson, T. S. (1969). Mathematical statistics: A decision theoretical approach. New York: Academic Press.

    Google Scholar 

  • Lindley, D. V. (1985). Making decisions (2nd ed.). Chichester, UK: Wiley.

    Google Scholar 

  • Neyman, J., & Pearson, E. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society of London Series A, 231, 289–337.

    CrossRef  Google Scholar 

  • Longford, N. (2005). Editorial: Model selection and efficiency. Is ‘Which model..?’ the right question? Journal of the Royal Statistical Society Series A, 168, 469–472.

    MathSciNet  CrossRef  Google Scholar 

  • Longford, N. T. (2007). Playing consequences [Letter to the Editor]. Significance, 4, 46.

    Google Scholar 

  • Longford, N. T. (2008). An alternative analysis of variance. SORT, Journal of the Catalan Institute of Statistics, 32, 77–91.

    Google Scholar 

  • R Development Core Team (2009). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

    Google Scholar 

  • Raiffa, H., & Schlaifer, R. (1961). Applied statistical decision theory. Boston, MA: Harvard Business School.

    Google Scholar 

  • Savage, L. J. (1951). The theory of statistical decision. Journal of the American Statistical Association, 46, 55–67.

    CrossRef  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. SNTL and Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain

    Nicholas T. Longford

Authors
  1. Nicholas T. Longford
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Correspondence to Nicholas T. Longford .

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Longford, N.T. (2013). Introduction. In: Statistical Decision Theory. SpringerBriefs in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40433-7_1

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