Advances in contemporary statistics and econometrics [electronic resource] : festschrift in honor of Christine Thomas-Agnan / Abdelaati Daouia, Anne Ruiz-Gazen, editors.

3 B-Spline Model-Assisted Estimator for Complex Parameters
4 B-Spline Imputation for Handling Item Nonresponse
References
Computational Outlier Detection Methods in Sliced Inverse Regression
1 Introduction
2 A Brief Review on Usual SIR
3 Outlier Detection Methods in SIR
3.1 A Naive Method
3.2 TTR Method
3.3 BOOT Method
4 A Numerical Example
4.1 Description of the Simulated Dataset
4.2 Numerical Results
5 Simulation Results
6 A Real Data Application
7 Concluding Remarks and Extensions
References
Uncoupled Isotonic Regression with Discrete Errors
1 Introduction
2 Estimation in Uncoupled Regression with Discrete Errors
3 Comparison with Coupled Isotonic Regression
4 Additional Proofs
References
Quantiles and Expectiles
Partially Linear Expectile Regression Using Local Polynomial Fitting
1 Introduction
2 Partially Linear Expectile Regression
3 Statistical Estimation Methodology
3.1 Estimation of the Vector of Regression Coefficients
3.2 Estimation of the Nonparametric Part
4 Asymptotic Properties and Bandwidth Selection
4.1 Optimal Theoretical Bandwidth (Matrix)
4.2 Rule-of-Thumb (ROT) Bandwidth Selector
5 Simulation Study
5.1 Simulation Results for Model 1
5.2 Simulation Results for Model 2
6 Real Data Application
7 Further Reading
References
Piecewise Linear Continuous Estimators of the Quantile Function
1 Introduction
2 The Piecewise Quantile Estimators
2.1 Definition
2.2 First Properties
2.3 Mean Integrated Squared Error
3 Discussion
Appendix
References
Single-Index Quantile Regression Models for Censored Data
1 Introduction
2 Model and Estimation
3 Asymptotic Results
4 Bandwidth Selection
5 Numerical Results
6 Case Study
References
Extreme Lp-quantile Kernel Regression.

1 Introduction
2 Lp-quantile Kernel Regression
3 Main Results
3.1 Intermediate Lp-quantile Regression
3.2 Extreme Lp-quantile Regression
3.3 Lp-quantile-Based Estimation of the Conditional Tail Index
4 Simulation Study
5 Real Data Example
6 Appendix
6.1 Preliminary Results
6.2 Proofs of Main Results
References
Robust Efficiency Analysis of Public Hospitals in Queensland, Australia
1 Introduction
2 Methodology
2.1 Theoretical Concepts
2.2 Nonparametric Estimators
3 Variables and Data
4 Results and Discussions
4.1 Univariate Input-Output Illustration
4.2 Main Analysis: Multiple Inputs Case
5 Concluding Remarks
References
On the Behavior of Extreme d-dimensional Spatial Quantiles Under Minimal Assumptions
1 Introduction
2 Results
3 Proofs
References
Modelling Flow in Gas Transmission Networks Using Shape-Constrained Expectile Regression
1 Introduction
2 Description of Data and Motivation
2.1 Data
2.2 Previous Models and Advantages of the New Approach
3 Methods
3.1 Geoadditive Regression Models
3.2 Shape-Constrained P-splines
3.3 Semiparametric Expectile Regression
4 Estimating and Forecasting Gas Flow
4.1 Results
4.2 Risk Analysis
5 Conclusion
References
Spatial Statistics and Econometrics
Asymptotic Analysis of Maximum Likelihood Estimation of Covariance Parameters for Gaussian Processes: An Introduction with Proofs
1 Introduction
2 Framework and Notations
2.1 Gaussian Processes and Covariance Functions
2.2 Classical Families of Covariance Functions
2.3 Maximum Likelihood
3 Increasing-Domain Asymptotics
3.1 Consistency
3.2 Asymptotic Normality
4 Fixed-Domain Asymptotics
4.1 What Changes
4.2 Microergodic and Non-microergodic Parameters.

4.3 Consistent Estimation of the Microergodic Parameter of the Isotropic Matérn Model
5 Conclusion
References
Global Scan Methods for Comparing Two Spatial Point Processes
1 Introduction
2 Methodology
2.1 Spatial Scan Statistics for Bivariate Data
2.2 Significance Issues
3 Applications
3.1 Simulation Study
3.2 Forest Fire Occurrences
4 Discussion
References
Assessing Spillover Effects of Spatial Policies with Semiparametric Zero-Inflated Models and Random Forests
1 Introduction
2 Conditional Average Treatment Effect, Identification and Model Specification
2.1 Identification Issues and Conditional Independence Assumption
2.2 Zero Inflation and Conditional Mixtures
3 Econometric Modeling and Estimation Procedures
3.1 A Flexible Semi-parametric Modeling Approach Based on Additive Models and Conditional Mixtures
3.2 Estimation of the Conditional Treatment Effect with Random Forests
4 An Illustration on the Estimation of the Effect of Local Development Policies in France
4.1 Description of the Policy and Data
4.2 Estimation Results and Counterfactual Analysis at the Municipality Level
5 Conclusion
References
Spatial Autocorrelation in Econometric Land Use Models: An Overview
1 Introduction
2 Econometric Land Use Models
3 Linear Land Use Models
3.1 Land Use Share Models
3.2 Spatial Autocorrelation in Linear Models
3.3 Example of Spatial Land Studies with Linear Models
4 Discrete Choice Land Use Models
4.1 Individual Choice Land Use Model
4.2 Spatial Autocorrelation in Discrete Choice Models
4.3 Examples of Spatial Land Use Studies with Discrete Choice Models
5 Land Use and Its Impacts on the Environment
5.1 Land Use and ES
5.2 Land Use and Water Quality
5.3 Land Use and Climate Change
6 Conclusion
References.

Modeling Dependence in Spatio-Temporal Econometrics
1 Introduction
2 Spatio-Temporal Statistics
2.1 Uncertainty and Data
2.2 Uncertainty and Models
2.3 Conditional Probabilities in a Hierarchical Statistical Model (HM)
2.4 ``Classical'' Statistical Modeling
3 Spatio-Temporal-Econometric Modeling
3.1 Spatial Description and Temporal Dynamics: A Simple Example
3.2 Time Series of Spatial Processes
3.3 Space-Time Autoregressive Moving Average (STARMA) Models
4 Spatial-Econometric Modeling
5 Modern Spatio-Temporal-Econometric Hierarchical Models
6 Concluding Remarks
References
Guidelines on Areal Interpolation Methods
1 Introduction
1.1 Motivation
1.2 Context
2 Notations
3 Data
3.1 Target Zones
3.2 First Source Scale: The Cells
3.3 Second Source Scale: The Iris
3.4 Variables to Estimate
4 Point-in-Polygon Method
4.1 Extensive Variables
4.2 Intensive Variables
4.3 Limitation of the Point-in Polygon Method
5 Areal Weighting Interpolation Method
5.1 Extensive Variable
5.2 Intensive Variable
6 Dasymetric Method with Auxiliary Variable X
6.1 Extensive Variables
6.2 Intensive Variables
7 Dasymetric Method with Control Zones
7.1 Presentation of the Method
7.2 Comparison Between DAC and DAX
8 Regression Modelling
8.1 Covariates and Exploratory Analysis
8.2 Linear Modelling
8.3 Regression Tree
References
Predictions in Spatial Econometric Models: Application to Unemployment Data
1 Introduction
1.1 Related Literature
2 Notation, Models, and Prediction Formula
2.1 Notation and the Spatial Autoregressive Durbin Model
2.2 In-Sample and Out-of-Sample Units
2.3 In-Sample Prediction Formulas
2.4 Out-of-Sample Prediction Formulas
3 Application
3.1 Theoretical Explanations for Regional Unemployment Differentials.