Add to ORKGSome misconceptions about subjective probability and Bayesian inference exist, that can be obstacles for acceptance and use of these concepts in practice. The statement that 'humans are not natural Bayesian personalists' is discussed, together with a formal mistake inherent to preposterior analysis. The most important problem that has to be solved for practical acceptance is correct measurement of subjective probability, where the random variable of interest must be easily interpretable
In this dissertation I aim to clarify the concept of probability. There are three kinds of interpret...
Elicitation is a key task for subjectivist Bayesians. Although skeptics hold that elicitation cannot...
In this article we demonstrate how algorithmic probability theory is applied to situations that inv...
Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are ad...
This paper aims to make explicit the methodological conditions that should be satisfied for the Baye...
Subjective Bayesianism is a major school of uncertain reasoning and statistical inference. Yet, it i...
In this thesis, we investigate the properties of Bayesian methods. In particular, we want to give fr...
In this article, I will show how several observed biases in human probabilistic reasoning can be par...
International audienceWhilst Bayesian epistemology is widely regarded nowadays as our best theory of...
Criticisms of so called `subjective probability' come on the one hand from those who maintain that p...
As scientists and as technologists we should discard the idea of a ‘true’ or ‘objective’ probability...
none1noAlthough accredited by a great many people across a wide range of fields, the subjective int...
In 1963, Anscombe and Aumann demonstrated that the introduction of an objective randomizing device i...
In this paper we reply to recent comments in this Special Issue according to which subjective probab...
This paper presents the historical and philosophical definition of subjective probabilities (also ca...
In this dissertation I aim to clarify the concept of probability. There are three kinds of interpret...
Elicitation is a key task for subjectivist Bayesians. Although skeptics hold that elicitation cannot...
In this article we demonstrate how algorithmic probability theory is applied to situations that inv...
Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are ad...
This paper aims to make explicit the methodological conditions that should be satisfied for the Baye...
Subjective Bayesianism is a major school of uncertain reasoning and statistical inference. Yet, it i...
In this thesis, we investigate the properties of Bayesian methods. In particular, we want to give fr...
In this article, I will show how several observed biases in human probabilistic reasoning can be par...
International audienceWhilst Bayesian epistemology is widely regarded nowadays as our best theory of...
Criticisms of so called `subjective probability' come on the one hand from those who maintain that p...
As scientists and as technologists we should discard the idea of a ‘true’ or ‘objective’ probability...
none1noAlthough accredited by a great many people across a wide range of fields, the subjective int...
In 1963, Anscombe and Aumann demonstrated that the introduction of an objective randomizing device i...
In this paper we reply to recent comments in this Special Issue according to which subjective probab...
This paper presents the historical and philosophical definition of subjective probabilities (also ca...
In this dissertation I aim to clarify the concept of probability. There are three kinds of interpret...
Elicitation is a key task for subjectivist Bayesians. Although skeptics hold that elicitation cannot...
In this article we demonstrate how algorithmic probability theory is applied to situations that inv...