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分层分位模拟——理论、方法及应用（英文版）

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283.56 7.1折 398 全新

库存8件

江西南昌

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作者田茂再

出版社科学出版社

ISBN9787030699039

出版时间2024-03

装帧精装

开本16开

定价398元

货号29361548

上书时间2024-11-02

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Preface

Part I  QUANTILE REGRESSION MODELLING

Chapter 1  INEAR QUANTILE REGRESSION

1.1  Education: Mathematical Achievements

1.1.1  Introduction

1.1.2  Data

1.1.3  Estimation Results

1.1.4  Confidence Intervals and Related Interpretations

1.1.5  Conclusion

1.2  Large Sample Properties

1.3  Bibliographic Notes

Chapter 2  NONPARAMETRIC QUANTILE REGRESSION

2.1  Robust Local Approximation Method

2.1.1  Introduction

2.1.2  Consistency

2.1.3  Rate of Convergence

2.1.4  Asymptotic Distribution

2.1.5  Optimization of Estimate

2.1.6  Bibliographic Notes

2.2  Nonparametric Function Estimation

2.2.1  Introduction

2.2.2  Asymptotic Properties

2.2.3  Applications

2.2.4  Bibliographic Notes

2.3  Local Linear Quantile Regression

2.3.1  Introduction

2.3.2  Local Linear Check Function Minimization

2.3.3  Local Linear Double-Kernel Smoothing

2.3.4  Bibliographic Notes

Chapter 3  ADAPTIVE QUANTILE REGRESSION

3.1  Locally Constant Adaptive Quantile Regression

3.1.1  Introduction

3.1.2  Adaptive Estimation

3.1.3  Implementation

3.1.4  Theoretical Properties

3.1.5  Bibliographic Notes

3.2  Locally Linear Adaptive Quantile Regression

3.2.1  Introduction

3.2.2  Local Linear Adaptive Estimation

3.2.3  Algorithm

3.2.4  Theoretical Properties

3.2.5  Bibliographic Notes

Chapter 4  ADAPTIVE QUANTILES REGRESSION

4.1  Additive Conditional Quantiles with High-Dimensional Covariates

4.1.1  Introduction

4.1.2  Methodology

4.1.3  Asymptotic Behavior

4.1.4  Concluding Remarks

4.1.5  Bibliographic Notes

4.2  Nonparametric Estimation

4.2.1  Introduction

4.2.2  Estimator

4.2.3  Asymptotic Results

4.2.4  Conclusions

4.2.5  Bibliographic Notes

Chapter 5  QUANTILE REGRESSION BASED ON VARYINGCOEFFICIENT MODELS

5.1  Adaptive Quantile Regression Based on Varying-coefficient Models

5.1.1  Introduction

5.1.2  Adaptive Estimation

5.1.3  Theoretical Properties

5.1.4  Conclusion

5.1.5  Bibliographic Notes

5.2  Varying-coefficient Models with Heteroscedasticity

5.2.1  Introduction

5.2.2  Local Linear CQR-AQR Estimation

5.2.3  Local Quadratic CQR-AQR Estimation

5.2.4  Bandwidth Selection

5.2.5  Hypothesis Testing

5.2.6  Local m-polynomial CQR-AQR Estimation

5.2.7  Discussion

5.2.8  Bibliographic Notes

Chapter 6  SINGLE-INDEX QUANTILE REGRESSION

6.1  Single Index Models

6.1.1  Introduction

6.1.2  The Model and Estimation

6.1.3  Large Sample Properties

6.1.4  Conclusions

6.1.5  Bibliographic Notes

6.2  CQR for Varying Coefficient Single-index Models

6.2.1  Introduction

6.2.2  Quantile Regression

6.2.3  Composite Quantile Regression

6.2.4  Discussion

6.2.5  Bibliographic Notes

Chapter 7  QUANTILE AUTOREGRESSION

7.1  Introduction

7.2  The Model

7.2.1  Description of The Model

7.2.2  Properties

7.3  Estimation

7.4  Quantitle Monotonicity

7.5  Inference

7.5.1  Wald Process and Related Tests

7.5.2  Testing for Asymmetric Dynamics

7.5.3  Bibliographic Notes

Chapter 8  COMPOSITE QUANTILE REGRESSION

8.1  Composite Quantile and Model Selection

8.1.1  Introduction and Motivation

8.1.2  Composite Quantile Regression

8.1.3  Asymptotic Relative Efficiency

8.1.4  The CQR-oracular Estimator

8.1.5  Concluding Remarks

8.1.6  Bibliographic Notes

8.2  Local Quantile Regression

8.2.1  Introduction

8.2.2  Estimation of Regression Function

8.2.3  Estimation of Derivative

8.2.4  Local p-polynomial CQR Smoothing

8.2.5  Discussion

……

内容摘要
随着科学技术的迅猛发展，具有复杂分层结构的数据在现实生活中很普遍。能完全剖析这类数据，发觉该类数据表象下的潜在规律性对于统计学等科研领域很有意义。本书致力于介绍复杂分层数据分析前沿知识，侧重于分层分位回归理论、方法及其应用研究。内容主要包括三大块：分层数据建模、分位回归与分层-分位回归。主要涉及到线性分层分位回归模拟、非参数分层分位回归模拟、适应性分层分位回归模拟、可加性分层分位回归模拟、变系数分层分位回归模拟、单指数分层分位回归模拟、分层分位自回归模拟、复合分层分位回归模拟、高维分层分位回归模拟、分层分位回归模拟、分层样条分位回归模拟、分层线性分位回归模拟、分层半参数分位回归模拟、复合分层线性分位回归模拟、复合分层半参数分位回归模拟等。

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分层分位模拟——理论、方法及应用（英文版）

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