# Fiducial Inference Method

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A Fiducial Inference Method is a statistical inference method that performs inverse probability without calling on prior probability distribution.

**See:**Frequentist Inference, Bayesian Inference, Decision Theory, History of Statistics, Ronald Fisher.

## References

### 2017

- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/fiducial_inference Retrieved:2017-10-12.
**Fiducial inference**is one of a number of different types of statistical inference. These are rules, intended for general application, by which conclusions can be drawn from samples of data. In modern statistical practice, attempts to work with fiducial inference have fallen out of fashion in favour of frequentist inference, Bayesian inference and decision theory. However, fiducial inference is important in the history of statistics since its development led to the parallel development of concepts and tools in theoretical statistics that are widely used. Some current research in statistical methodology is either explicitly linked to fiducial inference or is closely connected to it.

### 2008

- (Upton & Cook, 2008) ⇒ Graham Upton, and Ian Cook. (2008). “A Dictionary of Statistics, 2nd edition revised." Oxford University Press. ISBN:0199541450
- QUOTE: A method of statistical inference proposed by Sir Ronald Fisher in 1930. Fisher’s aim was to prescribe an entirely objective procedure that avoided prior assumptions or hypotheses. Fisher’s approach is not easy to understand and continues to be the subject of discussion.

### 1967

- (Kalbfleisch & Sprott, 1967) ⇒ https://link.springer.com/article/10.1007/BF02923493.
- QUOTE: The concept of fiducial probability was introduced by Fisher (1930) as applied to the coefficient of correlation. Since then it has been discussed by means of various examples, such as in Fisher (1956), and has been the subject of much controversy and criticism. It is the purpose of this paper to examine fiducial probability in the light of these criticisms, and to consider alternative procedures designed to overcome them.