According to the Bayesian view, scientific hypotheses must be appraised in terms of their posterior probabilities relative to the available experimental data. Such posterior probabilities are derived from the prior probabilities of the hypotheses by applying Bayes'theorem. One of the most important problems arising within the Bayesian approach to scientific methodology is the choice of prior probabilities. Here this problem is considered in detail w.r.t. two applications of the Bayesian approach: (1) the theory of inductive probabilities (TIP) developed by Rudolf Carnap and other epistomologists and (2) the analysis of the multinational inferences provided by Bayesian statstics (BS). ... Zie: Summar
The Bayesian approach to probability and statistics is described, a brief history of Bayesianism is ...
Scientists perform experiments to collect evidence supporting one or another hypothesis or theory. E...
This chapter focuses on Bayesian methods and illustrates both the intrinsic unity of Bayesian thinki...
According to the Bayesian view, scientific hypotheses must be appraised in terms of their posterior ...
Below we will consider the relations between inductive logic and statistics. More specifically, we w...
My dissertation examines two kinds of statistical tools for taking prior information into account, a...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...
Veel onderzoeksresultaten worden met behulp van statistiek verkregen. Vaak worden deze resultaten re...
We introduce a new model for inductive inference, by combining a Bayesian approach for representing ...
ABSTRACT: Bayesianism and Inference to the best explanation (IBE) are two different models of infere...
The role of the inductive modelling process (IMP) seems to be of practical importance in Bayesian st...
Howson and Urbach (1996) wrote a carefully structured book supporting the Bayesian view of scienti c...
Proponents of Bayesian confirmation theory believe that they have the solution to a significant, rec...
Bayesian inference is a method of statistical inference in which all forms of uncertainty are expres...
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comp...
The Bayesian approach to probability and statistics is described, a brief history of Bayesianism is ...
Scientists perform experiments to collect evidence supporting one or another hypothesis or theory. E...
This chapter focuses on Bayesian methods and illustrates both the intrinsic unity of Bayesian thinki...
According to the Bayesian view, scientific hypotheses must be appraised in terms of their posterior ...
Below we will consider the relations between inductive logic and statistics. More specifically, we w...
My dissertation examines two kinds of statistical tools for taking prior information into account, a...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...
Veel onderzoeksresultaten worden met behulp van statistiek verkregen. Vaak worden deze resultaten re...
We introduce a new model for inductive inference, by combining a Bayesian approach for representing ...
ABSTRACT: Bayesianism and Inference to the best explanation (IBE) are two different models of infere...
The role of the inductive modelling process (IMP) seems to be of practical importance in Bayesian st...
Howson and Urbach (1996) wrote a carefully structured book supporting the Bayesian view of scienti c...
Proponents of Bayesian confirmation theory believe that they have the solution to a significant, rec...
Bayesian inference is a method of statistical inference in which all forms of uncertainty are expres...
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comp...
The Bayesian approach to probability and statistics is described, a brief history of Bayesianism is ...
Scientists perform experiments to collect evidence supporting one or another hypothesis or theory. E...
This chapter focuses on Bayesian methods and illustrates both the intrinsic unity of Bayesian thinki...