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Book Categories |
| Ch. 1 | Bayesian inference for causal effects | 1 |
| Ch. 2 | Reference analysis | 17 |
| Ch. 3 | Probability matching priors | 91 |
| Ch. 4 | Model selection and hypothesis testing based on objective probabilities and Bayes factors | 115 |
| Ch. 5 | Role of P-values and other measures of evidence in Bayesian analysis | 151 |
| Ch. 6 | Bayesian model checking and model diagnostics | 171 |
| Ch. 7 | The elimination of nuisance parameters | 193 |
| Ch. 8 | Bayesian estimation of multivariate location parameters | 221 |
| Ch. 9 | Bayesian nonparametric modeling and data analysis : an introduction | 245 |
| Ch. 10 | Some Bayesian nonparametric models | 279 |
| Ch. 11 | Bayesian modeling in the wavelet domain | 315 |
| Ch. 12 | Bayesian nonparametric inference | 339 |
| Ch. 13 | Bayesian methods for function estimation | 373 |
| Ch. 14 | MCMC methods to estimate Bayesian parametric models | 415 |
| Ch. 15 | Bayesian computation : from posterior densities to Bayes factors, marginal likelihoods, and posterior model probabilities | 437 |
| Ch. 16 | Bayesian modelling and inference on mixtures of distributions | 459 |
| Ch. 17 | Simulation based optimal design | 509 |
| Ch. 18 | Variable selection and covariance selection in multivariate regression models | 519 |
| Ch. 19 | Dynamic models | 553 |
| Ch. 20 | Bayesian thinking in spatial statistics | 589 |
| Ch. 21 | Robust Bayesian analysis | 623 |
| Ch. 22 | Elliptical measurement error models - a Bayesian approach | 669 |
| Ch. 23 | Bayesian sensitivity analysis in skew-elliptical models | 689 |
| Ch. 24 | Bayesian methods for DNA microarray data analysis | 713 |
| Ch. 25 | Bayesian biostatistics | 743 |
| Ch. 26 | Innovative Bayesian methods for biostatistics and epidemiology | 763 |
| Ch. 27 | Bayesian analysis of case-control studies | 793 |
| Ch. 28 | Bayesian analysis of ROC data | 821 |
| Ch. 29 | Modeling and analysis for categorical response data | 835 |
| Ch. 30 | Bayesian methods and simulation-based computation for contingency tables | 869 |
| Ch. 31 | Multiple events time data : a Bayesian recourse | 891 |
| Ch. 32 | Bayesian survival analysis for discrete data with left-truncation and interval censoring | 907 |
| Ch. 33 | Software reliability | 929 |
| Ch. 34 | Bayesian aspects of small area estimation | 965 |
| Ch. 35 | Teaching Bayesian thought to nonstatisticians | 983 |
| Price | Condition | Delivery | Seller | Action |
| $291.00 | Digital |
| WonderClub |
Shane Flood
reviewed Handbook of Statistics: Bayesian Thinking, Modeling and Computation on October 21, 2014
Handbook of Statistics
I had studied the entirety of this textbook over the course of two university semesters. The textbook serves as a simple introduction, and delves unhurriedly and systemically into more advanced theories. A student will find an abundance of exercises to work through, and an adequate number of solved examples for almost each concept you come across in the chapters. As a bonus, I have absolutely enjoyed the case studies and articles included.
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