The theory of expected Utility by J. Von Neumann and O. Morgenstern

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1^ Langlois R.N. Coherence and Flexibility: Social Institutions in a World of Radical Uncertainty // Subjectivism, intelligibility and economic understanding / ed. I.M. Kirzner. – NY.: New York University Press, 1986. – P. 171–191

2^ Casella, G. and Berger, R.L. (2002) Statistical Inference. 2nd Edition, Duxbury Press, Pacific
Grove.

3^ Bernardo, J.M. and Smith, A.F.M. (1994) Bayesian Theory. John Wiley and Sons Inc., New
York. http://dx.doi.org/10.1002/9780470316870

4^ Sims, C.A. (2000) Using a Likelihood Perspective to Sharpen Econometric Discourse: Three
Examples. Journal of Econometrics, 95, 443-462.
http://dx.doi.org/10.1016/S0304-4076(99)00046-9

5^ Pawitan, Y. (2001) In All Likelihood: Statistical Modelling and Inference Using Likelihood.
Oxford Science Publications, Clarendon Press, Oxford.

6^ Pierce, D.A. and Peters, D. (1994) Higher-Order Asymptotics and the Likelihood Principle:
M. Brimacombe One Parameter Models. Biometrika, 81, 1-10. http://dx.doi.org/10.1093/biomet/81.1.1

7^ Frieden, B.R. (2004) Science from Fisher Information: A Unification. Cambridge University
Press, Cambridge, UK. http://dx.doi.org/10.1017/CBO9780511616907

8^ Akaike, H. (1981) Likelihood of a Model and Information Criteria. Journal of Econometrics, 16, 3-14. http://dx.doi.org/10.1016/0304-4076(81)90071-3

9^ Aeschbacher, S., Beaumont, M.A. and Futschik, A. (2012) A Novel Approach for Choosing
Summary Statistics in Approximate Bayesian Computation. Genetics, 192, 1027-1047.
http://dx.doi.org/10.1534/genetics.112.143164

10^ Luo, R., Hipp, A.L. and Larget, B. (2007) A Bayesian Model of AFLP Marker Evolution and
Phylogenetic Inference. Statistical Applications in Genetics and Molecular Biology, 88,
1813-1823.

11^ Berger, J.O. (1990) Robust Bayesian Analysis: Sensitivity to the Prior. Journal of Statistical
Planning and Inference, 25, 303-328. http://dx.doi.org/10.1016/0378-3758(90)90079-A