Time Series Analysis Time Series Analysis
    • ¥19,800

発行者による作品情報

A modern and accessible guide to the analysis of introductory time series data

Featuring an organized and self-contained guide, Time Series Analysis provides a broad introduction to the most fundamental methodologies and techniques of time series analysis. The book focuses on the treatment of univariate time series by illustrating a number of well-known models such as ARMA and ARIMA.

Providing contemporary coverage, the book features several useful and newlydeveloped techniques such as weak and strong dependence, Bayesian methods, non-Gaussian data, local stationarity, missing values and outliers, and threshold models. Time Series Analysis includes practical applications of time series methods throughout, as well as:
Real-world examples and exercise sets that allow readers to practice the presented methods and techniques Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout A companion website with additional data fi les and computer codes
Time Series Analysis is an excellent textbook for undergraduate and beginning graduate-level courses in time series as well as a supplement for students in advanced statistics, mathematics, economics, finance, engineering, and physics. The book is also a useful reference for researchers and practitioners in time series analysis, econometrics, and finance.

Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. He has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics. He is the author of Long-Memory Time Series: Theory and Methods, also published by Wiley.

ジャンル
科学/自然
発売日
2016年
4月28日
言語
EN
英語
ページ数
616
ページ
発行者
Wiley
販売元
John Wiley & Sons, Inc.
サイズ
18.4
MB
Bayesian Analysis of Time Series Bayesian Analysis of Time Series
2019年
Time Series for Data Science Time Series for Data Science
2022年
Dynamic Time Series Models using R-INLA Dynamic Time Series Models using R-INLA
2022年
Mathematical Methods in Survival Analysis, Reliability and Quality of Life Mathematical Methods in Survival Analysis, Reliability and Quality of Life
2013年
Data Analysis and Applications 1 Data Analysis and Applications 1
2019年
Statistics for Long-Memory Processes Statistics for Long-Memory Processes
2017年
Handbook of Regression Analysis With Applications in R Handbook of Regression Analysis With Applications in R
2020年
Reinsurance Reinsurance
2017年
Statistical Shape Analysis Statistical Shape Analysis
2016年
Multivariate Density Estimation Multivariate Density Estimation
2015年
Applied Longitudinal Analysis Applied Longitudinal Analysis
2012年
Applied Linear Regression Applied Linear Regression
2013年