Bayesian Thinking, Modeling and Computation
- 1st Edition, Volume 25 - December 22, 2005
- Latest edition
- Editors: Dipak K. Dey, C.R. Rao
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 4 - 5 1 5 3 9 - 1
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 4 6 1 1 7 - 5
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes… Read more
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians.
- Critical thinking on causal effects
- Objective Bayesian philosophy
- Nonparametric Bayesian methodology
- Simulation based computing techniques
- Bioinformatics and Biostatistics
Graduate students in Statistics, faculty and researchers interested in Bayesian philosophy and methodology, Scientists and Libraries
1. Bayesian Inference for Casual Effects (Donald B. Rubin)
2. Reference Analysis (Josè M. Bernardo)
3. Probability Matching Priors (Gauri Sankar Datta and Trevor J. Sweeting)
4. Model Selection and Hypothesis Testing Based on Objective Probabilities and Bayes Factors (Luis Raul Pericchi)
5. Role of P-values and other measures of evidence in Bayesian Analysis (Jayanta Ghosh, Sumitra Purkayastha and Tapas Samanta)
6. Bayesian Model Checking and Model Diagnostics (Hal S. Stern and Sandip Sinharay)
7. The Elimination of Nuisance Parameters (Brunero Liseo)
8. Bayesian Estimation of Multivariate Location Parameters (Ann Cohen Brandwein and William E. Strawdermann)
9. Bayesian Nonparametric Modeling and Data Analysis: An Introduction (Timothy E. Hanson, Adam J. Branscum and Wesley O. Johnson)
10. Some Bayesian Nonparametric Models (Paul Damien)
11. Bayesian Modeling in the Wavelet Domain (Fabrizio Ruggeri and Brani Vidakovic)
12. Bayesian Nonparametric Inference (Stephen Walker)
13. Bayesian Methods for Function Estimation (Nidhan Choudhuri, Subhashis Ghosal and Anindya Roy)
14. MCMC Methods to Estimate Bayesian Parametric Models (Antonietta Mira)
15. Bayesian Computation: From Posterior Densities to Bayes Factors, Marginal Likelihoods, and Posterior Model Probabilities (Ming-Hui Chen)
16. Bayesian Modelling and Inference on Mixtures of Distributions (Jean-Michel Marin, Kerrie Mengersen and Christian P. Robert)
17. Simulation Based Optimal Design (Peter Müller)
18. Variable Selection and Covariance Selection in Multivariate Regression Models (Edward Cripps, Chris Carter and Robert Kohn)
19. Dynamic Models (Helio S. Mignon, Dani Gamerman, Hedibert F. Lopes and Marco A.R. Ferreira)
20. Bayesian Thinking in Spatial Statistics (Lance A. Waller)
21. Robust Bayesian Analysis (Fabrizio Ruggeri, David Ríos Insua and Jacinto Martín)
22. Elliptical Measurement Error Models - A Bayesian Approach (Heleno Bolfarine and R.B. Arellano-Valle)
23. Bayesian Sensitivity Analysis in Skew-elliptical Models (Ignacio Vidal, Pilar Iglesias and Marcia Branco)
24. Bayesian Methods for DNA Microarray Data Analysis (Veerabhadran Baladandyuthapani, Shubhankar Ray and Bani Mallick)
25. Bayesian Biostatistics (David B. Dunson)
26. Innovative Bayesian Methods for Biostatistics and Epidemiology (Paul Gustafson, Shahadut Hossain and Lawrence McCandless)
27. Bayesian Analysis of Case-Control Studies (Bhramar Mukherjee, Samiran Sinha and Malay Ghosh)
28. Bayesian Analysis of ROC Data (Valen E. Johnson and Timothy D. Johnson)
29. Modeling and Analysis for Categorical Response Data (Siddhartha Chib)
30. Bayesian Methods and Simulation-Based Computation for Contingency Tables (James H. Albert)
31. Multiple Events Time Data: A Bayesian Recourse (Debajyoti Sinha and Sujit K. Ghosh)
32. Bayesian Survival Analysis for Discrete Data with Left-Truncation and Interval Censoring (Chong Z. He and Dongchu Sun)
33. Software Reliability (Lynn Kuo)
34. Bayesian Aspects of Small Area Estimation (Tapabrata Maiti)
35. Teaching Bayesian Thought to Nonstatisticians (Dalene K. Stangl)
2. Reference Analysis (Josè M. Bernardo)
3. Probability Matching Priors (Gauri Sankar Datta and Trevor J. Sweeting)
4. Model Selection and Hypothesis Testing Based on Objective Probabilities and Bayes Factors (Luis Raul Pericchi)
5. Role of P-values and other measures of evidence in Bayesian Analysis (Jayanta Ghosh, Sumitra Purkayastha and Tapas Samanta)
6. Bayesian Model Checking and Model Diagnostics (Hal S. Stern and Sandip Sinharay)
7. The Elimination of Nuisance Parameters (Brunero Liseo)
8. Bayesian Estimation of Multivariate Location Parameters (Ann Cohen Brandwein and William E. Strawdermann)
9. Bayesian Nonparametric Modeling and Data Analysis: An Introduction (Timothy E. Hanson, Adam J. Branscum and Wesley O. Johnson)
10. Some Bayesian Nonparametric Models (Paul Damien)
11. Bayesian Modeling in the Wavelet Domain (Fabrizio Ruggeri and Brani Vidakovic)
12. Bayesian Nonparametric Inference (Stephen Walker)
13. Bayesian Methods for Function Estimation (Nidhan Choudhuri, Subhashis Ghosal and Anindya Roy)
14. MCMC Methods to Estimate Bayesian Parametric Models (Antonietta Mira)
15. Bayesian Computation: From Posterior Densities to Bayes Factors, Marginal Likelihoods, and Posterior Model Probabilities (Ming-Hui Chen)
16. Bayesian Modelling and Inference on Mixtures of Distributions (Jean-Michel Marin, Kerrie Mengersen and Christian P. Robert)
17. Simulation Based Optimal Design (Peter Müller)
18. Variable Selection and Covariance Selection in Multivariate Regression Models (Edward Cripps, Chris Carter and Robert Kohn)
19. Dynamic Models (Helio S. Mignon, Dani Gamerman, Hedibert F. Lopes and Marco A.R. Ferreira)
20. Bayesian Thinking in Spatial Statistics (Lance A. Waller)
21. Robust Bayesian Analysis (Fabrizio Ruggeri, David Ríos Insua and Jacinto Martín)
22. Elliptical Measurement Error Models - A Bayesian Approach (Heleno Bolfarine and R.B. Arellano-Valle)
23. Bayesian Sensitivity Analysis in Skew-elliptical Models (Ignacio Vidal, Pilar Iglesias and Marcia Branco)
24. Bayesian Methods for DNA Microarray Data Analysis (Veerabhadran Baladandyuthapani, Shubhankar Ray and Bani Mallick)
25. Bayesian Biostatistics (David B. Dunson)
26. Innovative Bayesian Methods for Biostatistics and Epidemiology (Paul Gustafson, Shahadut Hossain and Lawrence McCandless)
27. Bayesian Analysis of Case-Control Studies (Bhramar Mukherjee, Samiran Sinha and Malay Ghosh)
28. Bayesian Analysis of ROC Data (Valen E. Johnson and Timothy D. Johnson)
29. Modeling and Analysis for Categorical Response Data (Siddhartha Chib)
30. Bayesian Methods and Simulation-Based Computation for Contingency Tables (James H. Albert)
31. Multiple Events Time Data: A Bayesian Recourse (Debajyoti Sinha and Sujit K. Ghosh)
32. Bayesian Survival Analysis for Discrete Data with Left-Truncation and Interval Censoring (Chong Z. He and Dongchu Sun)
33. Software Reliability (Lynn Kuo)
34. Bayesian Aspects of Small Area Estimation (Tapabrata Maiti)
35. Teaching Bayesian Thought to Nonstatisticians (Dalene K. Stangl)
- Edition: 1
- Latest edition
- Volume: 25
- Published: December 22, 2005
- Language: English
DD
Dipak K. Dey
Affiliations and expertise
University of Connecticut, CT, USACR
C.R. Rao
book “Ancient Inhabitants of Jebel Moya” published by the Cambridge Press under the joint authorship of Rao and two anthropologists. On the basis of work done at CU during the two year period, 1946-1948, Rao earned a Ph.D. degree and a few years later Sc.D. degree of CU and the rare honor of life fellowship of Kings College, Cambridge.
He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao’s Orthogonal arrays used in quality control, Rao’s score test, Rao’s Quadratic Entropy used in ecological work, Rao’s metric and distance which are incorporated in most statistical books.
He is the author of 10 books, of which two important books are, Linear Statistical Inference which is translated into German, Russian, Czec, Polish and Japanese languages,and Statistics and Truth which is translated into, French, German, Japanese, Mainland Chinese, Taiwan Chinese, Turkish and Korean languages.
He directed the research work of 50 students for the Ph.D. degrees who in turn produced 500 Ph.D.’s. Rao received 38 hon. Doctorate degree from universities in 19 countries spanning 6 continents. He received the highest awards in statistics in USA,UK and India: National Medal of Science awarded by the president of USA, Indian National Medal of Science awarded by the Prime Minister of India and the Guy Medal in Gold awarded by the Royal Statistical Society, UK. Rao was a recipient of the first batch of Bhatnagar awards in 1959 for mathematical sciences and and numerous medals in India and abroad from Science Academies. He is a Fellow of Royal Society (FRS),UK, and member of National Academy of Sciences, USA, Lithuania and Europe. In his honor a research Institute named as CRRAO ADVANCED INSTITUTE OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE was established in the campus of Hyderabad University.
Affiliations and expertise
University of Hyderabad Campus, IndiaRead Bayesian Thinking, Modeling and Computation on ScienceDirect