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Statistics

Info-gap theory is highly suited to deal with estimation and inference under severe uncertainty. Several applications have been developed in which info-gap theory augments statistical methods by dealing with non-random uncertainty.

  • Yakov Ben-Haim, 2006, Info-Gap Decision Theory: Decisions Under Severe Uncertainty, 2nd edition, Academic Press, London.
    Section 3.2.13: Estimating an uncertain probability density.

  • Yakov Ben-Haim, 2010, Info-Gap Economics: An Operational Introduction, Palgrave-Macmillan.
    Chapter 6: Estimation and Forecasting:
         Section 6.1: Regression prediction.
         Section 6.2: Auto-regression and data revision.
         Section 6.3: Confidence intervals.

  • Yakov Ben-Haim, Interpreting null results from measurements with uncertain correlations: An info-gap approach, to appear in Risk Analysis-An International Journal. Preprint.

  • Tania Mirer and Yakov Ben-Haim, Reliability Assessment of Explosive Material Based on Penalty Tests: An Info-Gap Approach, Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, to appear. Abstract.   Pre-print.

  • Yakov Ben-Haim, 2009, Info-gap forecasting and the advantage of sub-optimal models, European Journal of Operational Research, 197: 203-213. pdf file. Click here for a link to EJOR.

  • David R. Fox, Yakov Ben-Haim, Keith R. Hayes, Michael McCarthy, Brendan Wintle, Piers Dunstan, 2007, An info-gap approach to power and sample size calculations, Environmetrics, vol. 18, pp.189-203.

  • Miriam Zacksenhouse, Simona Nemets, Anna Yoffe, Yakov Ben-Haim, Mikhail Lebedev, Miguel Nicolelis, An info-gap approach to linear regression, IEEE International conference on Acoustics, Speech and Signal Processing, ICASSP 2006, May 14-19, 2006, Toulouse, France, Vol.3, pp.800-803.

  • Ferson, S. and W.T. Tucker, 2008, Probability boxes as info-gap models, Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS 2008, Article number 4531314. Abstract.

  • Berleant, D., Villaverde, K. and Koseheleva, O.M., 2008, Towards a more realistic representation of uncertainty: An approach motivated by Info-Gap Decision Theory, Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS 2008, Article number 4531297. Abstract.

  • Miriam Zacksenhouse, Simona Nemets, Miikhail A Lebedev and Miguel A Nicolelis, 2009, Robust Satisficing Linear Regression: performance/robustness trade-off and consistency criterion, Mechanical Systems and Signal Processing, vol. 23, pp.1954-1964, Abstract.

  • Yakov Ben-Haim, Tests of the Mean with Distributional Uncertainty: An Info-Gap Approach, 6th International Symposium on Imprecise Probability: Theories and Applications, Durham, United Kingdom, 14-18 July 2009.

Questions or comments on info-gap theory? Contact me at yakov@technion.ac.il