UID:
edoccha_9961612704202883
Format:
1 online resource (281 pages)
Edition:
1st ed.
ISBN:
3-031-65723-3
Series Statement:
Contributions to Statistics Series
Note:
Intro -- Preface -- Contents -- REML for Two-Dimensional P-Splines -- 1 Introduction -- 2 Sparse Mixed Models for P-Splines -- 3 Back Transformation from Mixed Models to P-Splines -- 4 An Application and Comparison of Computation Times -- 5 Discussion -- References -- Learning Bayesian Networks from Ordinal Data - The Bayesian Way -- 1 Introduction -- 2 Mathematical Details -- 2.1 Bayesian Networks -- 2.2 Gaussian Bayesian Networks (BGe Score) -- 2.3 New Bayesian Network Model (`BoB Method') -- 2.4 MCMC Inference -- 2.5 Sampling the Latent (Unobserved) Gaussian Values -- 2.6 Simulation Details -- 3 Empirical Results -- 4 Conclusion -- References -- Latent Dirichlet Allocation and Hidden Markov Models to Identify Public Perception of Sustainability in Social Media Data -- 1 Introduction -- 2 Methods -- 3 Data and Analysis Framework -- 4 Preliminary Results and Discussions -- References -- Bayesian Approaches to Model Overdispersion in Spatio-Temporal Binomial Data -- 1 Introduction -- 2 Methods -- 3 Application -- 4 Conclusions -- References -- Elicitation of Priors for Intervention Effects in Educational Trial Data -- 1 Introduction -- 2 Methodology -- 3 Manual Elicitation of Priors from Evaluation Reports -- 4 Results -- References -- Addressing Covariate Lack in Unit-Level Small Area Models Using GAMLSS -- 1 The Core of the Problem -- 2 The Proposal -- 2.1 Non-parametric Bootstrap -- 3 Simulation Results -- 4 Application and Concluding Remarks -- References -- Optimism Correction of the AUC with Complex Survey Data -- 1 Introduction -- 2 Methods -- 3 Simulation Study -- 3.1 Results -- 4 Conclusions -- References -- Statistical Models for Patient-Centered Outcomes in Clinical Studies -- 1 Introduction -- 2 A Statistical Model for DAOH -- 3 Analysis -- 3.1 Results -- 3.2 Model Interpretation -- 4 Discussion -- References.
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Bayesian Hidden Markov Models for Early Warning -- 1 Introduction -- 2 Model -- 3 Markov Chain Monte Carlo Algorithm -- 4 Real Data Application -- References -- A Bayesian Markov-Switching for Smooth Modelling of Extreme Value Distributions -- 1 Introduction -- 2 Markov-Switching Model Settings -- 3 Application to Energy Prices in Spain -- 4 Conclusions -- References -- Derivatives of the Log of a Determinant -- 1 Introduction -- 2 Theory -- 3 Applications -- References -- Monitoring Viral Infections in Severe Acute Respiratory Syndrome Patients in Brazil -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Discussion -- References -- A Computationally Efficient Spatio-Temporal Fusion Model for Reflectance Data -- 1 Introduction -- 2 Methodology -- 3 Application to Lake Garda Dataset -- 4 Simulation Study -- 5 Conclusion -- References -- Spatial Confounding in Gradient Boosting -- 1 Introduction -- 2 Gradient Boosting with Spatial+ -- 3 Simulation Study -- 4 Data Application -- 5 Conclusion -- References -- Adaptive Generalized Logistic Lasso and Its Application to Rankings in Sports -- 1 Introduction -- 2 Adaptive Generalized Logistic Lasso via Conic Programming -- 3 Simulation -- 4 Ranking in Sports -- 5 Summary -- References -- A Biclustering Approach via Mixture of Latent Trait Analyzers for the Analysis of Digital Divide in Italy -- 1 Introduction -- 2 Data -- 3 The MLTA Model for Biclustering -- 4 Results -- 5 Conclusions -- References -- Shrinkage in a Bayesian Panel Data Model with Time-Varying Coefficients -- 1 Introduction -- 2 Model Specification -- 2.1 Panel Data Model with Time-Varying Regression Effects -- 2.2 Latent Variable Model -- 2.3 Posterior Inference -- 3 Simulation Study -- 4 Case Study: Mother's Yearly Income -- 5 Conclusion -- References -- Integrating Single Index Effects in Generalized Additive Models -- 1 Introduction.
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2 Incorporating Single Index Effects into Generalised Additive Models -- 3 GefCom2014 Data Application -- 4 Conclusions -- References -- An Underrated Prior Distribution for Proportions. The Logistic-Normal for Dynamical Football Predictions -- 1 Introduction -- 2 Data -- 2.1 Methodology -- 2.2 Model Specification -- 2.3 Teams Merits -- 3 Results -- 4 Discussion -- References -- A Comparison of Extreme Gradient and Gaussian Process Boosting for a Spatial Logistic Regression on Satellite Data -- 1 Extreme Gradient Boosting -- 2 Gaussian Process Boosting -- 3 Model Specification and Experimental Design -- 4 Results -- 5 Discussion -- References -- Gene Coexpression Analysis with Dirichlet Mixture Model: Accelerating Model Evaluation Through Closed-Form KL Divergence Approximation Using Variational Techniques -- 1 Introduction -- 2 Methods -- 2.1 KL Divergence: Monte Carlo Approach -- 2.2 KL Divergence: Variational Approach -- 3 Results -- 4 Conclusion -- References -- Optimizing Variable Selection in Multi-Omics Datasets: A Focus on Exclusive Lasso -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Simulation Studies -- 3.2 Down Syndrome Analysis -- 4 Conclusion -- References -- Non-parametric Frailty Model for the Natural History of Prostate Cancer -- Using Data from a Screening Trial -- 1 Introduction -- 2 Methods -- 2.1 Longitudinal Submodel -- 2.2 Multi-state Model -- 2.3 Likelihood Function -- 3 Application -- References -- Parametric and Non-parametric Bayesian Imputation for Right Censored Survival Data -- 1 Introduction -- 2 Methods -- 2.1 Parametric Bayesian Approach -- 2.2 Non-parametric Bayesian Approach -- 3 Simulation -- 4 Application -- 5 Conclusion -- References -- An Updated Wilcoxon-Mann-Whitney Test -- 1 Introduction -- 2 Mid-quantiles and Mid p-Values -- 3 Application to the Wilcoxon-Mann-Whitney Test -- 3.1 Attainment Rates.
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4 Power -- 5 Conclusion -- References -- Estimating a Lower Bound of the Population Size in Capture-Recapture Experiments with Right Censored Data -- 1 Introduction -- 2 The Model -- 3 Examples of Application -- References -- Inference for Quasi-reaction Models with Covariate-Dependent Rates -- 1 Introduction -- 2 Latent Event History Model -- 3 Simulation Study: SIR System Under Lockdown -- 4 Epidemic Modelling of COVID-19 -- 5 Conclusion -- References -- Modelling of Overdispersed Count Rates -- 1 Introduction -- 2 Motivating Example -- 3 Negative Binomial Rate Models -- 4 Extensions -- 5 Discussion -- References -- Sparse Intrinsic Gaussian Processes for Prediction on Manifolds: Extending Applications to Environmental Contexts -- 1 Introduction -- 2 Construction of Sparse Intrinsic GP -- 2.1 Numerical Approximation of the Heat Kernel -- 2.2 Sparse Method DIC Used for Intrinsic GP -- 3 Implementation of Sparse Intrinsic GP -- 3.1 The Sparse Intrinsic GP on the U-Shape Domain -- 3.2 Impacted Predictive Distribution -- 4 Discussion -- References -- Functional Copula Graphical Regression Model for Analysing Brain-Body Rhythm -- 1 Introduction -- 2 Metodology -- 3 Analysis -- 3.1 Measurement Protocol -- 3.2 Graph Estimation -- 3.3 Model Selection and Results -- 4 Conclusion -- References -- State-Space Models for Clustering of Compositional Trajectories -- 1 Introduction -- 2 State Space Representations for Compositions -- 3 ECM Algorithm for Model-Based Clustering -- 4 Application -- 5 Ongoing Research -- References -- Approximated Gaussian Random Field Under Different Parameterizations for MCMC -- 1 Introduction -- 2 Spatial Modelling -- 2.1 The SPDE Method -- 2.2 Spatial Random Field Parameterization -- 3 Simulation -- 3.1 Simulation Results -- 4 Real Application: Index of Relative Abundance for Pollock -- 4.1 Real Application Results.
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5 Conclusion -- References -- Shape Analysis of AF Segments for Rapid Assessment of Mohs Layers for BCC Presence by AF-Raman Microscopy -- 1 Motivation and Objectives -- 2 Data -- 3 Methods, Related Work -- 4 Results and Discussion -- References -- Additive Mixed Models for Location, Scale and Shape via Gradient Boosting Techniques -- 1 Overview -- 2 Methods -- 2.1 Model Formulation -- 2.2 Boosting Algorithm -- 2.3 Computational Details -- 3 Cystis Fibrosis Application -- 4 Outlook -- References -- Regression Analysis with Missing Data Using Interval Imputation -- 1 Introduction -- 2 Interval Imputation -- 3 Bayesian Analysis -- 3.1 Point Estimation from Intervals -- 4 Illustration -- 4.1 Synthetic Dataset -- 4.2 Naval Propulsion Plants Data Set -- 5 Conclusion -- References -- Models of Network Delay -- 1 Introduction -- 2 Queuing Theory and Related Work -- 3 Notation and Convolution -- 4 Combination of Gamma Random Variables -- 5 Fits to Real Data -- 5.1 Data Set -- 5.2 Fits to Data -- 5.3 Estimating the Latency Shift -- 6 Conclusion -- References -- Estimating Dose and Time of Exposure from a Protein-Based Radiation Biomarker -- 1 Introduction -- 2 A Model Linking Calibration Curves with Foci Decay -- 3 Parameter Elicitation -- 4 Simulation Test Results -- 5 Real Data Bootstrap Test Results -- 6 Conclusion -- References -- Statistical Modelling for Big and Little Data -- 1 Introduction -- 2 Big Data -- 3 Little Data -- 4 Big and Little Data -- References -- Semi-Markov Multistate Model with Interval-Censored Transition Times -- 1 Introduction -- 2 Methodology -- 2.1 General Framework -- 2.2 Semi-Markov Multistate Modeling Approach -- 2.3 Interval-Censored Transition Times from Intermediate States -- 3 Three-Wave COVID-19 Data -- 4 Conclusions -- References -- A Distance-Based Statistic for Goodness-of-Fit Assessment -- 1 Introduction.
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2 Material and Methods.
Additional Edition:
ISBN 3-031-65722-5
Language:
English
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