In this essay, I argue about the relevance and the ultimate unity of the Bayesian approach in a neutral and agnostic manner. My main theme is that Bayesian data analysis is an effective tool for handling complex models, as proven by the increasing proportion of Bayesian studies in the applied sciences. I thus disregard the philosophical debates on the meaning of probability and on the random nature of parameters as things of the past that ultimately do a disservice to the approach and are irrelevant to most bystanders
The purpose of this article is to present the basic principles of the Bayesian approach to statistic...
AbstractBayesian and non-Bayesian approaches to statistical inference and decision-making are discus...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...
In this essay, I argue about the relevance and the ultimate unity of the Bayesian approach in a neut...
This paper is written in conjunction with the 3rd Bayesian econometrics meeting that took place at t...
Bayesians and non-Bayesians, often called frequentists, seem to be perpetually at loggerheads on fun...
I agree with Rob Kass’ point that we can and should make use of statistical methods developed under ...
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular a...
The thesis is an exposition and defence of Bayesianism as the preferred methodology of reasoning und...
A substantial school in the philosophy of science identifies Bayesian inference with inductive infer...
The Bayesian approach to probability and statistics is described, a brief history of Bayesianism is ...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal me...
Medical research makes intensive use of statistics in order to support its claims. In this paper we ...
This article explains the foundational concepts of Bayesian data analysis using virtually no mathema...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
The purpose of this article is to present the basic principles of the Bayesian approach to statistic...
AbstractBayesian and non-Bayesian approaches to statistical inference and decision-making are discus...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...
In this essay, I argue about the relevance and the ultimate unity of the Bayesian approach in a neut...
This paper is written in conjunction with the 3rd Bayesian econometrics meeting that took place at t...
Bayesians and non-Bayesians, often called frequentists, seem to be perpetually at loggerheads on fun...
I agree with Rob Kass’ point that we can and should make use of statistical methods developed under ...
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular a...
The thesis is an exposition and defence of Bayesianism as the preferred methodology of reasoning und...
A substantial school in the philosophy of science identifies Bayesian inference with inductive infer...
The Bayesian approach to probability and statistics is described, a brief history of Bayesianism is ...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal me...
Medical research makes intensive use of statistics in order to support its claims. In this paper we ...
This article explains the foundational concepts of Bayesian data analysis using virtually no mathema...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
The purpose of this article is to present the basic principles of the Bayesian approach to statistic...
AbstractBayesian and non-Bayesian approaches to statistical inference and decision-making are discus...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...