Add to ORKGCollecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses o
https://stat4astro2017.sciencesconf.org/International audienceThis book includes the lectures given ...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
This book is a selection of peer-reviewed contributions presented at the third Bayesian Young Statis...
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide vari...
The present book of Statistics and Data Science provides an accessible introduction to statistics fo...
Since 1990, Bayesian statistical methods have undergone major advances, both in estimation technique...
Bayesian methodology differs from traditional statistical methodology which involves frequentist app...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
2013 marked the 250th anniversary of the presentation of Bayes’ theorem by the philosopher Richard P...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
This chapter provides a general overview of Bayesian statistical methods. Topics include the notion ...
Due to great applications in various fields, such as social science, biomedicine, genomics, and sign...
Bayesian networks are powerful tools for representing relations of dependence among variables of a d...
https://stat4astro2017.sciencesconf.org/International audienceThis book includes the lectures given ...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
This book is a selection of peer-reviewed contributions presented at the third Bayesian Young Statis...
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide vari...
The present book of Statistics and Data Science provides an accessible introduction to statistics fo...
Since 1990, Bayesian statistical methods have undergone major advances, both in estimation technique...
Bayesian methodology differs from traditional statistical methodology which involves frequentist app...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
2013 marked the 250th anniversary of the presentation of Bayes’ theorem by the philosopher Richard P...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
This chapter provides a general overview of Bayesian statistical methods. Topics include the notion ...
Due to great applications in various fields, such as social science, biomedicine, genomics, and sign...
Bayesian networks are powerful tools for representing relations of dependence among variables of a d...
https://stat4astro2017.sciencesconf.org/International audienceThis book includes the lectures given ...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...