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Bayesian Statistics from Methods to Models and Applications

Overview of attention for book
Cover of 'Bayesian Statistics from Methods to Models and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Bayesian Survival Model Based on Moment Characterization
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    Chapter 2 A New Finite Approximation for the NGG Mixture Model: An Application to Density Estimation
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    Chapter 3 Distributed Estimation of Mixture Models
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    Chapter 4 Jeffreys’ Priors for Mixture Estimation
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    Chapter 5 A Subordinated Stochastic Process Model
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    Chapter 6 Bayesian Variable Selection for Generalized Linear Models Using the Power-Conditional-Expected-Posterior Prior
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    Chapter 7 Application of Interweaving in DLMs to an Exchange and Specialization Experiment
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    Chapter 8 On Bayesian Based Adaptive Confidence Sets for Linear Functionals
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    Chapter 9 Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Predictive Check
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    Chapter 10 A New Strategy for Testing Cosmology with Simulations
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    Chapter 11 Formal and Heuristic Model Averaging Methods for Predicting the US Unemployment Rate
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    Chapter 12 Bayesian Estimation of the Aortic Stiffness based on Non-invasive Computed Tomography Images
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    Chapter 13 Bayesian Filtering for Thermal Conductivity Estimation Given Temperature Observations
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    Chapter 14 A Mixture Model for Filtering Firms’ Profit Rates
Attention for Chapter 14: A Mixture Model for Filtering Firms’ Profit Rates
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Citations

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Chapter title
A Mixture Model for Filtering Firms’ Profit Rates
Chapter number 14
Book title
Bayesian Statistics from Methods to Models and Applications
Published by
Springer, Cham, January 2015
DOI 10.1007/978-3-319-16238-6_14
Book ISBNs
978-3-31-916237-9, 978-3-31-916238-6
Authors

Ellis Scharfenaker, Gregor Semieniuk

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 67%
Other 1 33%
Readers by discipline Count As %
Economics, Econometrics and Finance 2 67%
Mathematics 1 33%

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