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Tests with Repeated Observations

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References

  1. A. Wald, Sequential Analysis.New York: J. Wiley & Sons, 1947.Reprinted by Dover Publ., Mineola, NY, 2004.

    MATH  Google Scholar 

  2. S. Kullback, Information Theory and Statistics.New York: J. Wiley & Sons, 1959.Reprinted by Dover Publ., Mineola, NY, 1968.

    MATH  Google Scholar 

  3. N. Seshadri and C.-E.W. Sundberg, “List Viterbi decoding algorithms with applications,” IEEE Trans. Commun., vol.42, pp.313–323, Feb. Apr. 1994.

    Article  Google Scholar 

  4. S.-I. Amari and H. Nagaoka, Methods of Information Geometry.Providence, RI: American Mathematical Soc., 2000.

    MATH  Google Scholar 

  5. T.M. Cover and J.A. Thomas, Elements of Information Theory, 2nd edition.New York: J. Wiley & Sons, 2006.

    Google Scholar 

  6. H. Chernoff, “A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations,” Annals Math. Statist., vol.23, pp. 493–507, 1952.

    Article  MathSciNet  MATH  Google Scholar 

  7. H. Cramér, “Sur un nouveau théoréme-limite de la théorie des probabilités,” in Actalités Scientifiques et Industrielles, vol.736, Paris: Hermann, 1938.

    Google Scholar 

  8. A. Dembo and O. Zeitouni, Large Deviations Techniques and Applications, Second Edition.New York: Springer Verlag, 1998.

    Google Scholar 

  9. F.den Hollander, Large Deviations.Providence, RI: American Mathematical Soc., 2000.

    MATH  Google Scholar 

  10. K.L. Chung, A Course in Probability Theory, Second Edition.New York: Academic Press, 1968.

    Google Scholar 

  11. D. Bertsekas, A. Nedic, and A.E. Ozdaglar, Convex Analsis and Optimization.Belmont, MA: Athena Scientific, 2003.

    Google Scholar 

  12. J.R. Magnus and H.Neudecker, Matrix Differential Calculus with Applications in Statistics and Econometrics.Chichester, England: J. Wiley & Sons, 1988.

    MATH  Google Scholar 

  13. M. Basseville, “Information: Entropies, divergences et moyennes,” Tech. Rep. 1020, Institut de Recherche en Informatique et Systémes Aléatoires, Rennes, France, May 1996.

    Google Scholar 

  14. H.L. Van Trees, Detection, Estimation and Modulation Theory, Part I:Detection, Estimation and Linear Modulation Theory. New York: J. Wiley & Sons, 1968. paperback reprint edition in 2001.

    Google Scholar 

  15. A.G. Dabak, A Geometry for Detection Theory. PhD thesis, Electrical and Computer Engineering Dept., RiceUniversity, Houston, TX, 1992.

    Google Scholar 

  16. A.G. Dabak and D.H. Johnson, “Geometrically based robust detection,” inProc. Conf. Information Sciences and Systems, (Baltimore, MD),pp.73–77, The Johns Hopkins Univ., Mar. 1993.

    Google Scholar 

  17. K.J. Arrow, D. Blackwell, and M.A. Girshick, “Bayes and minimax solutions ofsequential decision problems,” Econometrica, vol.17, pp.213–244,Jul.-Oct. 1949.

    Article  MathSciNet  Google Scholar 

  18. M.H. DeGroot, Optimal Statistical Decisions. New York: McGraw-Hill, 1970. Reprinted by Wiley-Interscience, New York, 2004.

    MATH  Google Scholar 

  19. D. Bertsekas, Dynamic Programming and Optimal Control, Vol. I. Belmont, MA: Athena Scientific, 1995.

    Google Scholar 

  20. T.S. Ferguson, Mathematical Statistics: A Decision Theoretic Approach. New York: Academic Press, 1967.

    MATH  Google Scholar 

  21. S. Karlin and H.M. Taylor, A First Course in Stochastic Processes. New York: Academic Press, 1975.

    MATH  Google Scholar 

  22. R.G. Gallager, Discrete Stochastic Processes. Boston: Kluwer Acad. Publ., 1996.

    Google Scholar 

  23. D.L. Burkholder and R.A. Wijsman, “Optimum properties and admissibility ofsequential tests,” Annals. Math. Statistics, vol.34, pp.1–17, Mar.1963.

    Article  MathSciNet  MATH  Google Scholar 

  24. D.H. Johnson, “Notes for ELEC 530: Detection Theory.” Dept. Elec. Comp.Eng., Rice University, 2003.

    Google Scholar 

  25. P. Whittle, Optimization Over Time, Vol. II. Chichester, England: J. Wiley & Sons, 1983.

    Google Scholar 

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Levy, B.C. (2008). Tests with Repeated Observations. In: Principles of Signal Detection and Parameter Estimation. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76544-0_3

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  • DOI: https://doi.org/10.1007/978-0-387-76544-0_3

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