Abstract
Among the several schools of thought of the theory of inference two main groups are now clearly recognizable: Those that define the probability of an event as the limit of its relative frequency when independent identical trials of a random experiment are performed, and those that define probability in some other way. We shall agree to call the former group Frequentist and the latter Bayesian, only for identification purposes. The need for an alternative theory of probability arose in practice to handle situations when there was relevant prior information concerning the problem under scrutiny or when repeated trials were practically or theoretically impossible to perform.
This research was supported in part by PHS grant number 1-R01-CA41171-01A1 awarded by the National Cancer Institute, DHHS.
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References
Box, G.E.P., & Tiao, G.C. 1973. Bayesian Inference in statistical Analysis. Addison-Wesley, Reading.
Jeffreys, H. 1961. Theory of Probability. Oxford University Press, London.
Mandelbrot, B.B. (1977). Fractals: Form, chance, and dimension. San Francisco, Freeman.
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© 1988 Kluwer Academic Publishers
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Rodriguez, C.C. (1988). Understanding Ignorance. In: Erickson, G.J., Smith, C.R. (eds) Maximum-Entropy and Bayesian Methods in Science and Engineering. Fundamental Theories of Physics, vol 31-32. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3049-0_9
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DOI: https://doi.org/10.1007/978-94-009-3049-0_9
Publisher Name: Springer, Dordrecht
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