Abstract
Info-metrics is the science and practice of inference and quantitatively processing information. In this paper I provide a brief discussion of the state of info-metrics. After defining and discussing the concept of information and types of information I relate these concepts to information processing and data analysis. The connection between info-metrics and the class of information-theoretic methods of inference is discussed here as well. The discussion concludes with a partial list of open questions in info-metrics.
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References
Agmon, N., Alhassid, Y., Levine, R.D.: An Algorithm for Finding the Distribution of Maximal Entropy. Journal of Computational Physics 30, 250–259 (1979)
Cover, T.M., Thomas, J.A.: Elements of Information Theory, 2nd edn. John Wiley & Sons, New York (2006)
Cressie, N., Read, T.R.C.: Multinomial goodness-of-fit tests. J. Royal Stat. Soc. B 46, 440–464 (1984)
Floridi, L.: The Philosophy of Information. Oxford University Press, Oxford (2011)
Gokhale, D.V., Kullback, S.: The Information in Contingency Tables. Marcel Dekker, New York (1978)
Golan, A.: Information and Entropy Econometrics - A Review and Synthesis. Foundations and Trends®in Econometric 2(1-2), 1–145 (2008)
Golan, A., Gzyl, H.: An Entropic Estimator for Linear Inverse Problems. Entropy 14(5), 892–923 (2012)
Golan, A., Judge, G.:: Recovering and Processing Information in the Case of Underdetermined Economic Inverse Models, UC Berkeley (1992)
Golan, A., Judge, G., Miller, D.: Maximum Entropy Econometrics: Robust Estimation with Limited Data. John Wiley & Sons, New York (1996)
Hartley, R.V.L.: Transmission of Information. Bell System Technical Journal, 535–563 (July 1928)
Imbens, G.W., Johnson, P., Spady, R.H.: Information-Theoretic Approaches to Inference in Moment Condition Models. Econometrica 66, 333–357 (1998)
Jaynes, E.T.: Information Theory and Statistical Mechanics. Physics Review 106, 620–630 (1957a)
Jaynes, E.T.: Information Theory and Statistical Mechanics II. Physics Review 108, 171–190 (1957b)
Judge, G., Mittelhammer, R.: An Information Theoretic Approach to Econometrics. Cambridge University Press (2011)
Kitamura, Y.: Empirical Likelihood Methods in econometrics: Theory and Practice, Cowles Foundation Discussion Paper No. 1569 (2006)
Kitamura, Y., Stutzer, M.: An Information Theoretic Alternative to Generalized Method of Moments Estimation. Econometrica 65(4), 861–874 (1997)
Kullback, S., Leibler, R.A.: On information and sufficiency. The Annals of Math. Stat. 22, 79–86 (1951)
Owen, A.: Empirical Likelihood for Linear Models. The Annals of Statistics 19(4), 1725–1747 (1991)
Owen, A.: Empirical Likelihood. Chapman & Hall/CRC (2001)
Qin, J., Lawless, J.: Empirical Likelihood and General Estimating Equations. The Annals of Statistics 22, 300–325 (1994)
Renyi, A.: On measures of information and entropy. In: Proceedings of the Fourth Berkeley Symposium on Mathematics, Statistics and Probability 1960, vol. I, 547 (1961)
Shannon, C.E.: A Mathematical Theory of Communication. Bell System Technical Journal 27, 379–423 (1948)
Smith, R.J.: Empirical Likelihood Estimation and Inference. In: Salmon, M., Marriott, P. (eds.) Applications of Differential Geometry to Econometrics, pp. 119–150. Cambridge University Press (2000)
Tsallis, C.: Possible generalization of Boltzmann-Gibbs statistics. J. Stat. Phys. 52, 479–487 (1988)
Zellner, A.: The Bayesian Method of Moments (BMOM): Theory and Applications. In: Fomby, T., Hill, R.C. (eds.) Advances in Econometrics (1997)
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Golan, A. (2013). On the State of the Art of Info-metrics. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S., Suriya, K. (eds) Uncertainty Analysis in Econometrics with Applications. Advances in Intelligent Systems and Computing, vol 200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35443-4_1
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DOI: https://doi.org/10.1007/978-3-642-35443-4_1
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