9780691145327 - bayesian non- and semi-parametric methods and applications (the econometric and tinbergen institutes lectures) de rossi, peter (19 resultados)

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Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Editorial: Princeton University Press, Princeton, NJ, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Idioma: Inglés
Editorial: Princeton University Press, US, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Hardback. Condición: New. 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 n…atural 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 of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility.This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.

Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Condición: New. Reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. This book advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. Series: The Ec…onometric and Tinbergen Institutes Lectures. Num Pages: 224 pages, 66 line illus. BIC Classification: PBTB. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 151 x 217 x 22. Weight in Grams: 412. . 2014. Hardcover. . . . .

Idioma: Inglés
Editorial: Princeton University Press, US, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
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Hardback. Condición: New. 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 n…atural 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 of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility.This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.

Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
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Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
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Condición: New. Reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. This book advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. Series: The Ec…onometric and Tinbergen Institutes Lectures. Num Pages: 224 pages, 66 line illus. BIC Classification: PBTB. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 151 x 217 x 22. Weight in Grams: 412. . 2014. Hardcover. . . . . Books ship from the US and Ireland.

Idioma: Inglés
Editorial: 2014-01-01, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
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Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
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Paperback. Condición: New.

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Editorial: Princeton Univ Pr, 2014
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 272 pages. 9.00x6.00x1.00 inches. In Stock.

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Editorial: Princeton University Press, 2014
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Idioma: Inglés
Editorial: Princeton University Press, US, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
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Hardback. Condición: New. 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 n…atural 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 of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility.This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.

Idioma: Inglés
Editorial: Princeton University Press, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Idioma: Inglés
Editorial: Princeton University Press, US, 2014
Serie: Libro 3 de 6 - The Econometric and Tinbergen Institutes Lectures
- Tapa dura
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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Hardback. Condición: New. 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 n…atural 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 of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility.This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.