Bayesian Non Semi Parametric Methods by Rossi Peter (16 results)
Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, US, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Hardback. Condition: 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.
Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.
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Condition: 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. . . . .
Language: English
Published by Princeton University Press, US, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Hardback. Condition: 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.
Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Condition: 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.
Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
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Language: English
Published by Princeton University Press, US, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
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Hardback. Condition: 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.
Language: English
Published by Princeton University Press, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Condition: As New. Unread book in perfect condition.
Language: English
Published by Princeton University Press, US, 2014
Series: Book 3 of 6 - The Econometric and Tinbergen Institutes Lectures
- Hardcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Hardback. Condition: 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.
