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Published online by Cambridge University Press: 20 November 2018
For statistical inference on the unknown parameter θ of a probability distribution with a known form of its density function f(x | θ), the late Sir R. A. Fisher suggests that inference should be based on the observed value of a sufficient statistic when it exists. In the absence of a sufficient statistic, fiducial probability statements about θ can still be made, according to Fisher, if we can find an ancillary statistic so that "the most likely estimate could be made exhaustive by means of the ancillary values" [1, p. 138].