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Bayesian Non- and Semi-parametric Methods and Applications /

This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available,...

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Detalles Bibliográficos
Autor principal: Rossi, Peter E. (Peter Eric), 1955- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Princeton : Princeton University Press, [2014]
Colección:Book collections on Project MUSE.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Bayesian Non- and Semi-parametric Methods and Applications /   |c Peter E. Rossi. 
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490 0 |a The econometric and tinbergen institutes lectures 
505 0 |a 1.1. Finite Mixture of Normals Likelihood Function -- 1.2. Maximum Likelihood Estimation -- 1.3. Bayesian Inference for the Mixture of Normals Model -- 1.4. Priors and the Bayesian Model -- 1.5. Unconstrained Gibbs Sampler -- 1.6. Label-Switching -- 1.7. Examples -- 1.8. Clustering Observations -- 1.9. Marginalized Samplers -- \ 
505 0 |a 2.1. Dirichlet Processes-A Construction -- 2.2. Finite and Infinite Mixture Models -- 2.3. Stick-Breaking Representation -- 2.4. Polya Urn Representation and Associated Gibbs Sampler -- 2.5. Priors on DP Parameters and Hyper-parameters -- 2.6. Gibbs Sampler for DP Models and Density Estimation -- 2.7. Scaling the Data -- 2.8. Density Estimation Examples. 
505 0 |a 3.1. Joint vs. Conditional Density Approaches -- 3.2. Implementing the Joint Approach with Mixtures of Normals -- 3.3. Examples of Non-parametric Regression Using Joint Approach -- 3.4. Discrete Dependent Variables -- 3.5. An Example of Expenditure Function Estimation. 
505 0 |a 4.1. Semi-parametric Regression with DP Priors -- 4.2. Semi-parametric IV Models. 
505 0 |a 5.1. Introduction -- 5.2. Semi-parametric Random Coefficient Logit Models -- 5.3. An Empirical Example of a Semi-parametric Random Coefficient Logit Model. 
505 0 |a 6.1. When Are Non-parametric and Semi-parametric Methods Most Useful? -- 6.2. Semi-parametric or Non-parametric Methods? -- 6.3. Extensions. 
520 |a This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number. 
546 |a English. 
588 |a Description based on print version record. 
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650 7 |a Economics, Mathematical.  |2 fast  |0 (OCoLC)fst00902260 
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650 7 |a BUSINESS & ECONOMICS  |x Economics  |x General.  |2 bisacsh 
650 6 |a Theorie de la decision bayesienne. 
650 6 |a Économetrie. 
650 0 |a Economics, Mathematical. 
650 0 |a Bayesian statistical decision theory. 
650 0 |a Econometrics. 
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