عنوان

Empirical likelihood and quantile methods for time series :

(Number (ISBN

9789811001512

(Number (ISBN

9789811001529

(Number (ISBN

9789811001536

(Number (ISBN

9811001510

(Number (ISBN

9811001529

(Number (ISBN

9811001537

Erroneous ISBN

9789811001512

Title Proper

Empirical likelihood and quantile methods for time series :

General Material Designation

[Book]

Other Title Information

efficiency, robustness, optimality, and prediction /

First Statement of Responsibility

Yan Liu, Fumiya Akashi, Masanobu Taniguchi.

Place of Publication, Distribution, etc.

Singapore :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

[2018]

Date of Publication, Distribution, etc.

©2018

Specific Material Designation and Extent of Item

1 online resource

Series Title

Springer briefs in statistics. JSS research series in statistics

Text of Note

Includes bibliographical references and index.

Text of Note

Intro; Preface; Contents; 1 Introduction; 1.1 Stationary Time Series; 1.2 Prediction Problem; 1.3 Interpolation and Extrapolation Problem; 1.4 Robust Interpolation and Extrapolation; 2 Parameter Estimation Based on Prediction; 2.1 Introduction; 2.1.1 Location Disparity; 2.1.2 Scale Disparity; 2.1.3 A New Disparity Based on Prediction; 2.2 Fundamentals of the New Disparity; 2.3 Parameter Estimation Based on Disparity; 2.3.1 Finite Variance Innovations Case; 2.3.2 Infinite Variance Innovations Case; 2.4 Efficiency and Robustness; 2.4.1 Robustness Against the Fourth-Order Cumulant

Text of Note

5 Self-weighted GEL Methods for Infinite Variance Processes5.1 Introduction to Self-weighted Least Absolute Deviations Approach; 5.2 Self-weighted GEL Statistics; 5.3 Application to the Change Point Test; 5.4 Numerical Studies; 5.5 Auxiliary Results; Bibliography; ; Index

0

8

Text of Note

This book integrates the fundamentals of asymptotic theory of statistical inference for time series under nonstandard settings, e.g., infinite variance processes, not only from the point of view of efficiency but also from that of robustness and optimality by minimizing prediction error. This is the first book to consider the generalized empirical likelihood applied to time series models in frequency domain and also the estimation motivated by minimizing quantile prediction error without assumption of true model. It provides the reader with a new horizon for understanding the prediction problem that occurs in time series modeling and a contemporary approach of hypothesis testing by the generalized empirical likelihood method. Nonparametric aspects of the methods proposed in this book also satisfactorily address economic and financial problems without imposing redundantly strong restrictions on the model, which has been true until now. Dealing with infinite variance processes makes analysis of economic and financial data more accurate under the existing results from the demonstrative research. The scope of applications, however, is expected to apply to much broader academic fields. The methods are also sufficiently flexible in that they represent an advanced and unified development of prediction form including multiple-point extrapolation, interpolation, and other incomplete past forecastings. Consequently, they lead readers to a good combination of efficient and robust estimate and test, and discriminate pivotal quantities contained in realistic time series models.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9789811001529

International Standard Book Number

9789811001512

International Standard Book Number

9789811001536

Finance-- Econometric models.

Time-series analysis.

Statistical Theory and Methods.

Statistics for Business, Management, Economics, Finance, Insurance.

Statistics for Social Sciences, Humanities, Law.

Finance-- Econometric models.

MATHEMATICS-- Applied.

MATHEMATICS-- Probability & Statistics-- General.

Time-series analysis.

MAT-- 003000

MAT-- 029000

PBT

PBT

Number

Edition

Class number

Liu, Yan

Akashi, Fumiya

Taniguchi, Masanobu

Date of Transaction

20200823221337.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y