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[null,"1.","Record Nr.",null,"UNINA9910781932303321"]
[null,null,"Autore",null,"Woodward Phillip"]
[null,null,"Titolo",null,"Bayesian analysis made simple : an Excel GUI for WinBUGS / / Phil Woodward"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton, Fla. : , : CRC Press, , 2012"]
[null,null,"ISBN",null,"0-429-15195-0"]
[{"$nulls":4},"1-283-35030-0"]
[{"$nulls":4},"9786613350305"]
[{"$nulls":4},"1-4398-3955-7"]
[null,null,"Descrizione fisica",null,"1 online resource (364 p.)"]
[null,null,"Collana",null,"Chapman & Hall/CRC biostatistics series"]
[null,null,"Classificazione",null,"MAT029000"]
[null,null,"Disciplina",null,"519.5/42028553"]
[null,null,"Soggetti",null,"Bayesian statistical decision theory"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","A Chapman & Hall book."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Front Cover; Contents; Case Studies; Preface; Acknowledgments; Chapter 1: Brief Introduction to Statistics, Bayesian Methods, and WinBUGS; Chapter 2: BugsXLA Overview and Reference Manual; Chapter 3: Normal Linear Models; Chapter 4: Generalized Linear Models; Chapter 5: Normal Linear Mixed Models; Chapter 6: Generalized Linear Mixed Models; Chapter 7: Emax or Four-Parameter Logistic Non-Linear Models; Chapter 8: Bayesian Variable Selection; Chapter 9: Longitudinal and Repeated Measures Models; Chapter 10: Robust Models; Chapter 11: Beyond BugsXLA: Extending the WinBUGS Code"]
[{"$nulls":4},"Appendix A: Distributions Referenced in BugsXLAAppendix E: Troubleshooting; References; Back Cover"]
[null,null,null,"Sommario/riassunto","Although the popularity of the Bayesian approach to statistics has been growing for years, many still think of it as somewhat esoteric, not focused on practical issues, or generally too difficult to understand.Bayesian Analysis Made Simple is aimed at those who wish to apply Bayesian methods but either are not experts or do not have the time to create WinBUGS code and ancillary files for every analysis they undertake. Accessible to even those who would not routinely use Excel, this book provides a custom-made Excel GUI, immediately useful to those users who want to be able to quickly apply Bayesian methods without being distracted by computing or mathematical issues.From simple NLMs to complex GLMMs and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models "]
[{"$nulls":4},"in an intuitive manner accessible to the statistically savvy user. Packed with relevant case studies, this book is for any data analyst wishing to apply Bayesian methods to analyze their data, from professional statisticians to statistically aware scientists--"]