The Fisher Parametric Inference Problem
Concerning the identification of the parameters of a distribution law, the mature reader may recall lengthy disputes in the mid 20th century about the interpretation of their variability in terms of fiducial distribution (Fisher 1956), structural probabilities (Fraser 1966), priors/posteriors (Ramsey 1925), and so on. From an epistemology viewpoint, this entailed a companion dispute as to the nature of probability: is it a physical feature of phenomena to be described through random variables or a way of synthesizing data about a phenomenon? Opting for the latter, Fisher defines a fiducial distribution law of parameters of a given random variable that he deduces from a sample of its specifications. With this law he computes, for instance “the probability that μ (mean of a Gaussian variable – our note) is less than any assigned value, or the probability that it lies between any assigned values, or, in short, its probability distribution, in the light of the sample observed”.
Read more about this topic: Algorithmic Inference
Famous quotes containing the words fisher, inference and/or problem:
“I turn over a new leaf every day. But the blots show through.”
—Keith Waterhouse, British screenwriter, Willis Hall, and John Schlesinger. Billy Fisher (Tom Courtenay)
“I shouldn’t want you to be surprised, or to draw any particular inference from my making speeches, or not making speeches, out there. I don’t recall any candidate for President that ever injured himself very much by not talking.”
—Calvin Coolidge (1872–1933)
“The problem of culture is seldom grasped correctly. The goal of a culture is not the greatest possible happiness of a people, nor is it the unhindered development of all their talents; instead, culture shows itself in the correct proportion of these developments. Its aim points beyond earthly happiness: the production of great works is the aim of culture.”
—Friedrich Nietzsche (1844–1900)