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Complex Models and Computational Methods in Statistics

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Cover of 'Complex Models and Computational Methods in Statistics'

Table of Contents

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    Book Overview
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    Chapter 1 A New Unsupervised Classification Technique Through Nonlinear Non Parametric Mixed-Effects Models
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    Chapter 2 Estimation Approaches for the Apparent Diffusion Coefficient in Rice-Distributed MR Signals
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    Chapter 3 Longitudinal Patterns of Financial Product Ownership: A Latent Growth Mixture Approach
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    Chapter 4 Computationally Efficient Inference Procedures for Vast Dimensional Realized Covariance Models
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    Chapter 5 A GPU Software Library for Likelihood-Based Inference of Environmental Models with Large Datasets
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    Chapter 6 Theoretical Regression Trees: A Tool for Multiple Structural-Change Models Analysis
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    Chapter 7 Some Contributions to the Theory of Conditional Gibbs Partitions
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    Chapter 8 Estimation of Traffic Matrices for LRD Traffic
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    Chapter 9 A Newton’s Method for Benchmarking Time Series
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    Chapter 10 Spatial Smoothing for Data Distributed over Non-planar Domains
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    Chapter 11 Volatility Swings in the US Financial Markets
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    Chapter 12 Semicontinuous Regression Models with Skew Distributions
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    Chapter 13 Classification of Multivariate Linear-Circular Data with Nonignorable Missing Values
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    Chapter 14 Multidimensional Connected Set Detection in Clustering Based on Nonparametric Density Estimation
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    Chapter 15 Using Integrated Nested Laplace Approximations for Modelling Spatial Healthcare Utilization
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    Chapter 16 Supply Function Prediction in Electricity Auctions
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    Chapter 17 A Hierarchical Bayesian Model for RNA-Seq Data
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Citations

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Title
Complex Models and Computational Methods in Statistics
Published by
Springer Milan, January 2013
DOI 10.1007/978-88-470-2871-5
ISBNs
978-8-84-702870-8, 978-8-84-702871-5
Editors

Grigoletto, Matteo, Lisi, Francesco, Petrone, Sonia

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 19 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 30%
Student > Master 4 20%
Researcher 4 20%
Unspecified 2 10%
Professor > Associate Professor 2 10%
Other 2 10%
Readers by discipline Count As %
Mathematics 5 25%
Unspecified 3 15%
Computer Science 3 15%
Agricultural and Biological Sciences 3 15%
Business, Management and Accounting 1 5%
Other 5 25%

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