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Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data

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Cover of 'Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data'

Table of Contents

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    Book Overview
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    Chapter 1 Advances and Challenges in Inferences for Elliptically Contoured t Distributions
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    Chapter 2 Longitudinal Mixed Models with t Random Effects for Repeated Count and Binary Data
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    Chapter 3 Zero-Inflated Spatial Models: Application and Interpretation
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    Chapter 4 Inferences in Stochastic Volatility Models: A New Simpler Way
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    Chapter 5 A Generalization of the Familial Longitudinal Binary Model to the Multinomial Setup
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    Chapter 6 Dynamic Models for Longitudinal Ordinal Non-stationary Categorical Data
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    Chapter 7 Semi-parametric Models for Longitudinal Count, Binary and Multinomial Data
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    Chapter 8 Penalized Generalized Quasi-Likelihood Based Variable Selection for Longitudinal Data
Attention for Chapter 4: Inferences in Stochastic Volatility Models: A New Simpler Way
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Chapter title
Inferences in Stochastic Volatility Models: A New Simpler Way
Chapter number 4
Book title
Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data
Published by
Springer, Cham, January 2016
DOI 10.1007/978-3-319-31260-6_4
Book ISBNs
978-3-31-931258-3, 978-3-31-931260-6
Authors

Vickneswary Tagore, Nan Zheng, Brajendra C. Sutradhar

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