Add to ORKGThe work "Topics in non-parametric Bayesian statistics", by N.L.Hjort, presents recent advances in Bayesian nonparametrics. In my discussion, I point out further and open issues, in particular from a predictive point of view
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
The use of Bayesian nonparametrics models has increased rapidly over the last few decades driven by ...
This book demonstrates that nonparametric statistics can be taught from a parametric point of view. ...
The work "Topics in non-parametric Bayesian statistics", by N.L.Hjort, presents recent advances in B...
The intersection set of Bayesian and nonparametric statistics was almost empty until about 1973, but...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
The paper evaluates the usefulness of a nonparametric approach to Bayesian inference by presenting t...
This paper consists of three main parts. First, we give an introduction to Hill’s assumption A (n) a...
This thesis consists of five chapters on how to construct prediction sets for different types of dat...
Research on Bayesian nonparametric methods has received a growing interest for the past twenty years...
Research on Bayesian nonparametric methods has received a growing interest for the past twenty years...
In this talk I will discuss some recent progress in Bayesian nonparametric modeling and inference. ...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
The use of Bayesian nonparametrics models has increased rapidly over the last few decades driven by ...
This book demonstrates that nonparametric statistics can be taught from a parametric point of view. ...
The work "Topics in non-parametric Bayesian statistics", by N.L.Hjort, presents recent advances in B...
The intersection set of Bayesian and nonparametric statistics was almost empty until about 1973, but...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
Bayesian prediction is analyzed in the I.I.D case. In a search for robust methods we combine non par...
The paper evaluates the usefulness of a nonparametric approach to Bayesian inference by presenting t...
This paper consists of three main parts. First, we give an introduction to Hill’s assumption A (n) a...
This thesis consists of five chapters on how to construct prediction sets for different types of dat...
Research on Bayesian nonparametric methods has received a growing interest for the past twenty years...
Research on Bayesian nonparametric methods has received a growing interest for the past twenty years...
In this talk I will discuss some recent progress in Bayesian nonparametric modeling and inference. ...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
The use of Bayesian nonparametrics models has increased rapidly over the last few decades driven by ...
This book demonstrates that nonparametric statistics can be taught from a parametric point of view. ...