Howson and Urbach (1996) wrote a carefully structured book supporting the Bayesian view of scienti c reasoning, which includes an unfavorable judgment about the so-called objective Bayesian inference. In this paper, the theses of the book are investigated from Carnap's analytical viewpoint in the light of a new formulation of the Principle of Indi fference. In particular, the paper contests the thesis according to which no theory can adequately represent 'ignorance' between alternatives. Beginning from the new formulation of the principle, a criterion for the choice of an objective prior is suggested in the paper together with an illustration for the case of Binomial sampling. In particular, it will be shown that the new prior provides bett...
A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast l...
We discuss the problem of selecting among alternative parametric models within the Bayesian framewor...
A central problem facing a probabilistic approach to the problem of induction is the difficulty of s...
Howson and Urbach (1996) wrote a carefully structured book supporting the Bayesian view of scienti c...
Bayesianism and Inference to the best explanation (IBE) are two different models of inference. Recen...
ABSTRACT: Bayesianism and Inference to the best explanation (IBE) are two different models of infere...
What is a good prior? Actual prior knowledge should be used, but for complex models this is often no...
Research Doctorate - Doctor of Philosophy (PhD)Interval estimation of the Binomial parameter è, repr...
Abstract. General theoretical principles that enable the derivation of prior probabilities are of in...
Objective prior distributions represent an important tool that allows one to have the advantages of ...
In 1930, Fisher presented his fiducial argument as a solution to the "fundamen- tally false and devo...
Following the critical review of Seaman III et al (2012), we re ect onwhat is presumably the most es...
International audienceWhilst Bayesian epistemology is widely regarded nowadays as our best theory of...
According to the Bayesian view, scientific hypotheses must be appraised in terms of their posterior ...
Beta distributions with both parameters equal to 0, ½, or 1 are the usual choices for “noninformativ...
A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast l...
We discuss the problem of selecting among alternative parametric models within the Bayesian framewor...
A central problem facing a probabilistic approach to the problem of induction is the difficulty of s...
Howson and Urbach (1996) wrote a carefully structured book supporting the Bayesian view of scienti c...
Bayesianism and Inference to the best explanation (IBE) are two different models of inference. Recen...
ABSTRACT: Bayesianism and Inference to the best explanation (IBE) are two different models of infere...
What is a good prior? Actual prior knowledge should be used, but for complex models this is often no...
Research Doctorate - Doctor of Philosophy (PhD)Interval estimation of the Binomial parameter è, repr...
Abstract. General theoretical principles that enable the derivation of prior probabilities are of in...
Objective prior distributions represent an important tool that allows one to have the advantages of ...
In 1930, Fisher presented his fiducial argument as a solution to the "fundamen- tally false and devo...
Following the critical review of Seaman III et al (2012), we re ect onwhat is presumably the most es...
International audienceWhilst Bayesian epistemology is widely regarded nowadays as our best theory of...
According to the Bayesian view, scientific hypotheses must be appraised in terms of their posterior ...
Beta distributions with both parameters equal to 0, ½, or 1 are the usual choices for “noninformativ...
A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast l...
We discuss the problem of selecting among alternative parametric models within the Bayesian framewor...
A central problem facing a probabilistic approach to the problem of induction is the difficulty of s...