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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56) - Hardcover
- PublisherCambridge University Press
- Publication date2024
- ISBN 10 1009410067
- ISBN 13 9781009410069
- BindingHardcover
- Edition number1
- Number of pages306
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Generalized Additive Models for Location, Scale and Shape : A Distributional Regression Approach, With Applications
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Generalized Additive Models for Location, Scale and Shape (Hardcover)
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Book Description Hardcover. Condition: new. Hardcover. An emerging field in statistics, distributional regression facilitates the modelling of the complete conditional distribution, rather than just the mean. This book introduces generalized additive models for location, scale and shape (GAMLSS) one of the most important classes of distributional regression. Taking a broad perspective, the authors consider penalized likelihood inference, Bayesian inference, and boosting as potential ways of estimating models and illustrate their usage in complex applications. Written by the international team who developed GAMLSS, the text's focus on practical questions and problems sets it apart. Case studies demonstrate how researchers in statistics and other data-rich disciplines can use the model in their work, exploring examples ranging from fetal ultrasounds to social media performance metrics. The R code and data sets for the case studies are available on the book's companion website, allowing for replication and further study. This text provides a state-of-the-art treatment of distributional regression, accompanied by real-world examples from diverse areas of application. Maximum likelihood, Bayesian and machine learning approaches are covered in-depth and contrasted, providing an integrated perspective on GAMLSS for researchers in statistics and other data-rich fields. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781009410069
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56) by Stasinopoulos, Mikis D., Kneib, Thomas, Klein, Nadja, Mayr, Andreas, Heller, Gillian Z. [Hardcover ]
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56)
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(2024)
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ISBN 13: 9781009410069
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56)
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Generalized Additive Models for Location, Scale and Shape
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56)
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56)
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications
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Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications: 56 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 56)
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