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Developments in Statistical Modelling

Overview of attention for book
Developments in Statistical Modelling
Springer Nature Switzerland

Table of Contents

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    Book Overview
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    Chapter 1 REML for Two-Dimensional P-Splines
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    Chapter 2 Learning Bayesian Networks from Ordinal Data - The Bayesian Way
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    Chapter 3 Latent Dirichlet Allocation and Hidden Markov Models to Identify Public Perception of Sustainability in Social Media Data
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    Chapter 4 Bayesian Approaches to Model Overdispersion in Spatio-Temporal Binomial Data
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    Chapter 5 Elicitation of Priors for Intervention Effects in Educational Trial Data
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    Chapter 6 Addressing Covariate Lack in Unit-Level Small Area Models Using GAMLSS
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    Chapter 7 Optimism Correction of the AUC with Complex Survey Data
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    Chapter 8 Statistical Models for Patient-Centered Outcomes in Clinical Studies
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    Chapter 9 Bayesian Hidden Markov Models for Early Warning
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    Chapter 10 A Bayesian Markov-Switching for Smooth Modelling of Extreme Value Distributions
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    Chapter 11 Derivatives of the Log of a Determinant
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    Chapter 12 Monitoring Viral Infections in Severe Acute Respiratory Syndrome Patients in Brazil
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    Chapter 13 A Computationally Efficient Spatio-Temporal Fusion Model for Reflectance Data
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    Chapter 14 Spatial Confounding in Gradient Boosting
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    Chapter 15 Adaptive Generalized Logistic Lasso and Its Application to Rankings in Sports
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    Chapter 16 A Biclustering Approach via Mixture of Latent Trait Analyzers for the Analysis of Digital Divide in Italy
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    Chapter 17 Shrinkage in a Bayesian Panel Data Model with Time-Varying Coefficients
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    Chapter 18 Integrating Single Index Effects in Generalized Additive Models
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    Chapter 19 An Underrated Prior Distribution for Proportions. The Logistic–Normal for Dynamical Football Predictions
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    Chapter 20 A Comparison of Extreme Gradient and Gaussian Process Boosting for a Spatial Logistic Regression on Satellite Data
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    Chapter 21 Gene Coexpression Analysis with Dirichlet Mixture Model: Accelerating Model Evaluation Through Closed-Form KL Divergence Approximation Using Variational Techniques
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    Chapter 22 Optimizing Variable Selection in Multi-Omics Datasets: A Focus on Exclusive Lasso
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    Chapter 23 Non-parametric Frailty Model for the Natural History of Prostate Cancer; Using Data from a Screening Trial
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    Chapter 24 Parametric and Non-parametric Bayesian Imputation for Right Censored Survival Data
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    Chapter 25 An Updated Wilcoxon–Mann–Whitney Test
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    Chapter 26 Estimating a Lower Bound of the Population Size in Capture-Recapture Experiments with Right Censored Data
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    Chapter 27 Inference for Quasi-reaction Models with Covariate-Dependent Rates
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    Chapter 28 Modelling of Overdispersed Count Rates
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    Chapter 29 Sparse Intrinsic Gaussian Processes for Prediction on Manifolds: Extending Applications to Environmental Contexts
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    Chapter 30 Functional Copula Graphical Regression Model for Analysing Brain-Body Rhythm
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    Chapter 31 State-Space Models for Clustering of Compositional Trajectories
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    Chapter 32 Approximated Gaussian Random Field Under Different Parameterizations for MCMC
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    Chapter 33 Shape Analysis of AF Segments for Rapid Assessment of Mohs Layers for BCC Presence by AF-Raman Microscopy
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    Chapter 34 Additive Mixed Models for Location, Scale and Shape via Gradient Boosting Techniques
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    Chapter 35 Regression Analysis with Missing Data Using Interval Imputation
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    Chapter 36 Models of Network Delay
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    Chapter 37 Estimating Dose and Time of Exposure from a Protein-Based Radiation Biomarker
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    Chapter 38 Statistical Modelling for Big and Little Data
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    Chapter 39 Semi-Markov Multistate Model with Interval-Censored Transition Times
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    Chapter 40 A Distance-Based Statistic for Goodness-of-Fit Assessment
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Title
Developments in Statistical Modelling
Published by
Springer Nature Switzerland, July 2024
DOI 10.1007/978-3-031-65723-8
ISBNs
978-3-03-165722-1, 978-3-03-165723-8
Editors

Einbeck, Jochen, Maeng, Hyeyoung, Ogundimu, Emmanuel, Perrakis, Konstantinos

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