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Bayesian statistics and marketing [[electronic resource] /] / Peter E. Rossi, Greg M. Allenby, Robert McCulloch
| Bayesian statistics and marketing [[electronic resource] /] / Peter E. Rossi, Greg M. Allenby, Robert McCulloch |
| Autore | Rossi Peter E (Peter Eric), <1955-> |
| Edizione | [Reprinted with corrections.] |
| Pubbl/distr/stampa | Chichester, England, : J. Wiley, 2006, c2005 |
| Descrizione fisica | 1 online resource (372 p.) |
| Disciplina |
658.8
658.83015118 |
| Altri autori (Persone) |
AllenbyGreg M <1956-> (Greg Martin)
McCullochRobert E (Robert Edward) |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Bayesian statistical decision theory
Marketing research - Mathematical models Marketing - Mathematical models |
| ISBN |
1-280-59232-X
9786613622150 0-470-86369-2 0-470-86368-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Bayesian Statistics and Marketing; Contents; 1 Introduction; 1.1 A Basic Paradigm for Marketing Problems; 1.2 A Simple Example; 1.3 Benefits and Costs of the Bayesian Approach; 1.4 An Overview of Methodological Material and Case Studies; 1.5 Computing and This Book; Acknowledgements; 2 Bayesian Essentials; 2.0 Essential Concepts from Distribution Theory; 2.1 The Goal of Inference and Bayes' Theorem; 2.2 Conditioning and the Likelihood Principle; 2.3 Prediction and Bayes; 2.4 Summarizing the Posterior; 2.5 Decision Theory, Risk, and the Sampling Properties of Bayes Estimators
2.6 Identification and Bayesian Inference 2.7 Conjugacy, Sufficiency, and Exponential Families; 2.8 Regression and Multivariate Analysis Examples; 2.9 Integration and Asymptotic Methods; 2.10 Importance Sampling; 2.11 Simulation Primer for Bayesian Problems; 2.12 Simulation from the Posterior of the Multivariate Regression Model; 3 Markov Chain Monte Carlo Methods; 3.1 Markov Chain Monte Carlo Methods; 3.2 A Simple Example: Bivariate Normal Gibbs Sampler; 3.3 Some Markov Chain Theory; 3.4 Gibbs Sampler; 3.5 Gibbs Sampler for the Seemingly Unrelated Regression Model 3.6 Conditional Distributions and Directed Graphs 3.7 Hierarchical Linear Models; 3.8 Data Augmentation and a Probit Example; 3.9 Mixtures of Normals; 3.10 Metropolis Algorithms; 3.11 Metropolis Algorithms Illustrated with the Multinomial Logit Model; 3.12 Hybrid Markov Chain Monte Carlo Methods; 3.13 Diagnostics; 4 Unit-Level Models and Discrete Demand; 4.1 Latent Variable Models; 4.2 Multinomial Probit Model; 4.3 Multivariate Probit Model; 4.4 Demand Theory and Models Involving Discrete Choice; 5 Hierarchical Models for Heterogeneous Units; 5.1 Heterogeneity and Priors 5.2 Hierarchical Models 5.3 Inference for Hierarchical Models; 5.4 A Hierarchical Multinomial Logit Example; 5.5 Using Mixtures of Normals; 5.6 Further Elaborations of the Normal Model of Heterogeneity; 5.7 Diagnostic Checks of the First-Stage Prior; 5.8 Findings and Influence on Marketing Practice; 6 Model Choice and Decision Theory; 6.1 Model Selection; 6.2 Bayes Factors in the Conjugate Setting; 6.3 Asymptotic Methods for Computing Bayes Factors; 6.4 Computing Bayes Factors Using Importance Sampling; 6.5 Bayes Factors Using MCMC Draws; 6.6 Bridge Sampling Methods 6.7 Posterior Model Probabilities with Unidentified Parameters 6.8 Chib's Method; 6.9 An Example of Bayes Factor Computation: Diagonal Multinomial Probit Models; 6.10 Marketing Decisions and Bayesian Decision Theory; 6.11 An Example of Bayesian Decision Theory: Valuing Household Purchase Information; 7 Simultaneity; 7.1 A Bayesian Approach to Instrumental Variables; 7.2 Structural Models and Endogeneity/Simultaneity; 7.3 Nonrandom Marketing Mix Variables; Case Study 1: A Choice Model for Packaged Goods: Dealing with Discrete Quantities and Quantity Discounts; Background; Model; Data; Results Discussion |
| Record Nr. | UNINA-9910142573003321 |
Rossi Peter E (Peter Eric), <1955->
|
||
| Chichester, England, : J. Wiley, 2006, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Bayesian statistics and marketing [[electronic resource] /] / Peter E. Rossi, Greg M. Allenby, Robert McCulloch
| Bayesian statistics and marketing [[electronic resource] /] / Peter E. Rossi, Greg M. Allenby, Robert McCulloch |
| Autore | Rossi Peter E (Peter Eric), <1955-> |
| Edizione | [Reprinted with corrections.] |
| Pubbl/distr/stampa | Chichester, England, : J. Wiley, 2006, c2005 |
| Descrizione fisica | 1 online resource (372 p.) |
| Disciplina |
658.8
658.83015118 |
| Altri autori (Persone) |
AllenbyGreg M <1956-> (Greg Martin)
McCullochRobert E (Robert Edward) |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Bayesian statistical decision theory
Marketing research - Mathematical models Marketing - Mathematical models |
| ISBN |
1-280-59232-X
9786613622150 0-470-86369-2 0-470-86368-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Bayesian Statistics and Marketing; Contents; 1 Introduction; 1.1 A Basic Paradigm for Marketing Problems; 1.2 A Simple Example; 1.3 Benefits and Costs of the Bayesian Approach; 1.4 An Overview of Methodological Material and Case Studies; 1.5 Computing and This Book; Acknowledgements; 2 Bayesian Essentials; 2.0 Essential Concepts from Distribution Theory; 2.1 The Goal of Inference and Bayes' Theorem; 2.2 Conditioning and the Likelihood Principle; 2.3 Prediction and Bayes; 2.4 Summarizing the Posterior; 2.5 Decision Theory, Risk, and the Sampling Properties of Bayes Estimators
2.6 Identification and Bayesian Inference 2.7 Conjugacy, Sufficiency, and Exponential Families; 2.8 Regression and Multivariate Analysis Examples; 2.9 Integration and Asymptotic Methods; 2.10 Importance Sampling; 2.11 Simulation Primer for Bayesian Problems; 2.12 Simulation from the Posterior of the Multivariate Regression Model; 3 Markov Chain Monte Carlo Methods; 3.1 Markov Chain Monte Carlo Methods; 3.2 A Simple Example: Bivariate Normal Gibbs Sampler; 3.3 Some Markov Chain Theory; 3.4 Gibbs Sampler; 3.5 Gibbs Sampler for the Seemingly Unrelated Regression Model 3.6 Conditional Distributions and Directed Graphs 3.7 Hierarchical Linear Models; 3.8 Data Augmentation and a Probit Example; 3.9 Mixtures of Normals; 3.10 Metropolis Algorithms; 3.11 Metropolis Algorithms Illustrated with the Multinomial Logit Model; 3.12 Hybrid Markov Chain Monte Carlo Methods; 3.13 Diagnostics; 4 Unit-Level Models and Discrete Demand; 4.1 Latent Variable Models; 4.2 Multinomial Probit Model; 4.3 Multivariate Probit Model; 4.4 Demand Theory and Models Involving Discrete Choice; 5 Hierarchical Models for Heterogeneous Units; 5.1 Heterogeneity and Priors 5.2 Hierarchical Models 5.3 Inference for Hierarchical Models; 5.4 A Hierarchical Multinomial Logit Example; 5.5 Using Mixtures of Normals; 5.6 Further Elaborations of the Normal Model of Heterogeneity; 5.7 Diagnostic Checks of the First-Stage Prior; 5.8 Findings and Influence on Marketing Practice; 6 Model Choice and Decision Theory; 6.1 Model Selection; 6.2 Bayes Factors in the Conjugate Setting; 6.3 Asymptotic Methods for Computing Bayes Factors; 6.4 Computing Bayes Factors Using Importance Sampling; 6.5 Bayes Factors Using MCMC Draws; 6.6 Bridge Sampling Methods 6.7 Posterior Model Probabilities with Unidentified Parameters 6.8 Chib's Method; 6.9 An Example of Bayes Factor Computation: Diagonal Multinomial Probit Models; 6.10 Marketing Decisions and Bayesian Decision Theory; 6.11 An Example of Bayesian Decision Theory: Valuing Household Purchase Information; 7 Simultaneity; 7.1 A Bayesian Approach to Instrumental Variables; 7.2 Structural Models and Endogeneity/Simultaneity; 7.3 Nonrandom Marketing Mix Variables; Case Study 1: A Choice Model for Packaged Goods: Dealing with Discrete Quantities and Quantity Discounts; Background; Model; Data; Results Discussion |
| Record Nr. | UNINA-9910825632103321 |
|
Rossi Peter E (Peter Eric), <1955->
|
||
| Chichester, England, : J. Wiley, 2006, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||