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词条 时间序列分析实例研究
释义

《时间序列分析实例研究》是一本有关时间序列分析应用于实际的实证分析研究的专著。全书分为两大部分:第一部分简要介绍了时间序列分析的基础理论和方法。这些内容是读懂《时间序列分析实例研究》各案例研究所必备的基本知识;第二部分是案例研究。从中读者可看出时间序列分析是如何广泛地应用于实际并成为解决各种问题的核心工具。本书可作为应用时间序列分析领域的大学生和研究生教学参考书或补充教材,也是应用统计工作者和相关学科的科技人员、工程师很有价值的参考资料。

书名:时间序列分析实例研究

作者:谢忠杰

ISBN:9787506273077

类别:科学与自然

页数:282页

定价:¥45.00元

出版社:世界图书出版公司

出版时间:2006-12-01

装帧:平装

开本:16开

丛 书 名:科学前沿丛书

内容简介

书中的案例涉及到当年中国科学家从自己的观测记录中是如何发现天王星的光环的,滤波理论如何应用于中国东海和黄海的重力勘探,谱分析如何判别先天性愚型儿童的脑电特征、多元谱的K-L信息量如何应用于优秀飞行员的生理特征的检测,潜周期分析如何发现离体脑垂体仍有内分泌的节律周期。预测理论如何应用于气象的建模和预报,等等许多非常有趣而真实的研究案例。这些研究成果使作者获得了中国国家自然科学奖和国内外的多项奖项。

读者通过《时间序列分析实例研究》的学习不仅可学到时间序列分析的基本理论和方法.更重要的是《时间序列分析实例研究》介绍了”如何将一个实际问题转化成数学问题”,然后运用数学和统计学的理论和方法加以解决,这包括最后还原到实际,用实验数据加以检验的完整过程。

图书目录

Preface

PART ONE

An Introduction to the Theory and Methods of Time Series Analysis

Chapter 1.Theory of Stationary Time Series

1.1 The definition of stationary stochastic processes

1.2 The spectral representation of covariance function

1.3 The Hilbert space of second order processes

1.4 Stochastic integral and the isomorphic relationship between H~ and the functional space L2(dFe)

1.4.1 Orthogonal stochastic measure

1.4.2 Stochastic integral and the representation of stationary processes

1.4.3.Karhunen theorem

1.5 Strong law of large numbers for stationary series

1.6 Sampling theorem for stochastic stationary processes

Chapter 2.ARMA Model and Model Fitting

2.1 ARMA model and the Wold decomposition

2.2 Orthogonal basis in Hilbert space Hf

2.3 The covariance function of ARMA model and Yule-Walker equation

2.4 Model fitting under the criterion of one-step ahead prediction error

2.5 M.E.model fitting for observed data

2.5.1 M.E.model fitting with sample covariance

2.5.2 Order selection problem

Chapter 3.Prediction, Filtering and Spectral Analysis of Time Series

3.1 Prediction of time series

3.1.1 The prediction formula for AR models

3.1.2 The prediction formula for ARMA models

3.2 The linear filtering of time series

a.a Spectral analysis of time series

3.3.1 Theory and methods of hidden periodicities analysis

3.3.2 Theory and methods of spectral density estimations

PART TWO Case Studies in Time Series Analysis

Case I.Digital Processing of a Dynamic Marine Gravity Meter

1.Problem statement and working diagram of a dynamic marine gravity meter

2.The first test for solving the problem

3.Design a new digital filter under Min-Max criterion

4.The frequency rectification by filtering

5.Practical checking in the prospecting field of the East Sea of China

Case II.Digital Filters Design by Maximum Entropy Modelling

1.Problem statement

2.Design the filter by maximum entropy modelling

3.A practical filter design

Case III.The Spectral Analysis of the Visual Evoked Potentials of Normal and Congenital Dull Children (Down's disease)

1.Introduction

2.Spectral analysis of VEP records for dull and normal children

3.Statistical analysis for detection of characteristics

4.Physiological interpretation

Appendix III

Case IV.Statistical Analysis of VEP and AI by the Principal Component Analyis of Time Serise in Frequency Domain

Case V.Periodicity Analysis of LH Release in Isolated Pituitary Gland by Hidden Frequency Analysis

Case VI.Statistical Detection of Uranian Ring Signnals from the Light Curve of Photoelectric Observation

Case VII.On the Forecasting of Freight Transportation by a New Model Fitting Procedure of Time Series

Case VIII.The Water Flow Prediction in Xiang River

Case IX.Miscellaneous Cases Study

Bibliography

Subject Index

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