Applied time series analysis with R- Second Edition - Wayne Woodward-经管之家官网!

人大经济论坛-经管之家 收藏本站
您当前的位置> 考研考博>>

考研

>>

Applied time series analysis with R- Second Edition - Wayne Woodward

Applied time series analysis with R- Second Edition - Wayne Woodward

发布:chicu | 分类:考研

关于本站

人大经济论坛-经管之家:分享大学、考研、论文、会计、留学、数据、经济学、金融学、管理学、统计学、博弈论、统计年鉴、行业分析包括等相关资源。
经管之家是国内活跃的在线教育咨询平台!

经管之家新媒体交易平台

提供"微信号、微博、抖音、快手、头条、小红书、百家号、企鹅号、UC号、一点资讯"等虚拟账号交易,真正实现买卖双方的共赢。【请点击这里访问】

提供微信号、微博、抖音、快手、头条、小红书、百家号、企鹅号、UC号、一点资讯等虚拟账号交易,真正实现买卖双方的共赢。【请点击这里访问】

AppliedTimeSeriesAnalysiswithR2ndEditionISBN-10:1498734227ISBN-13:978-1498734226Virtuallyanyrandomprocessdevelopingchronologicallycanbeviewedasatimeseries.Ineconomicsclosingpricesofstocks,thecostofmon ...
免费学术公开课,扫码加入


Applied Time Series Analysis with R 2nd Edition
  • ISBN-10:1498734227
  • ISBN-13:978-1498734226

Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis with R, Second Edition includes examples across a variety of fields, develops theory, and provides an R-based software package to aid in addressing time series problems in a broad spectrum of fields. The material is organized in an optimal format for graduate students in statistics as well as in the natural and social sciences to learn to use and understand the tools of applied time series analysis.


Features

  • Gives readers the ability to actually solve significant real-world problems
  • Addresses many types of nonstationary time series and cutting-edge methodologies
  • Promotes understanding of the data and associated models rather than viewing it as the output of a "black box"
  • The versatility of the R.
  • Over 150 exercises and extensive support for instructors

The second edition includes additional real-data examples, uses R-based code that helps students easily analyze data, generate realizations from models, and explore the associated characteristics. It also adds discussion of new advances in the analysis of long memory data and data with Time-varying frequencies (TVF).


Editorial Reviews
Review

"What an extraordinary range of topics this book covers, all very insightfully. I like [the authors'] innovations very much, including the AR factor table." – David Findley, Senior Mathematical Statistician, US Census Bureau (retired)


"...improved coverage of the scope of time series analysis in both frequency and time domain ... ... I commend the authors for having included a number of topics on nonstationary processes (eg, time-varying spectrum, wavelets), ...an excellent textbook ..." ―Hernando Ombao, Journal of the American Statistical Association

" The book is a good introductory or reference text for practitioners or those new to time series analysis. The chapters are easy to read, and the distinction between applied and theoretical examples throughout helps to cement knowledge for these two distinct groups." ―Rebecca Killick ,Mathematics & Statistics Department, Lancaster University

" . . . this book has much to recommend it for that audience. Coverage is quite thorough and up to date. There is an emphasis on the selection and evaluation of models which is very welcome, and not always found in statistics textbooks directed at non -statisticians." ―Robert W. Hayden, Mathematical Association of America

"I find the structure of the book very convincing: First, the more basic models are spelled out, second, the forecasting purpose is dealt with, third, estimation and related inferential issues are covered, before an extension (to the multivariate case and more Demandinging models) is tackled. Each chapter concludes with an exercise section, typically containing theoretical problems as well as applied problems, where the latter build on R; moreover, R commands are explained in separate sections. Further, the book contains over 100 examples. " ― Uwe Hassler, Stat Papers


About the Author

Wayne A. Woodward is a professor and chair of the Department of Statistical Science at Southern Methodist University in Dallas, Texas.
Henry L. Gray is a C.F. Frensley Professor Emeritus in the Department of Statistical Science at Southern Methodist University in Dallas, Texas.
Alan C. Elliott is a biostatistician in the Department of Statistical Science at Southern Methodist University in Dallas, Texas.


「经管之家」APP:经管人学习、答疑、交友,就上经管之家!
免流量费下载资料----在经管之家app可以下载论坛上的所有资源,并且不额外收取下载高峰期的论坛币。
涵盖所有经管领域的优秀内容----覆盖经济、管理、金融投资、计量统计、数据分析、国贸、财会等专业的学习宝库,各类资料应有尽有。
来自五湖四海的经管达人----已经有上千万的经管人来到这里,你可以找到任何学科方向、有共同话题的朋友。
经管之家(原人大经济论坛),跨越高校的围墙,带你走进经管知识的新世界。
扫描下方二维码下载并注册APP
本文关键词:

本文论坛网址:https://bbs.pinggu.org/thread-6661681-1-1.html

人气文章

1.凡人大经济论坛-经管之家转载的文章,均出自其它媒体或其他官网介绍,目的在于传递更多的信息,并不代表本站赞同其观点和其真实性负责;
2.转载的文章仅代表原创作者观点,与本站无关。其原创性以及文中陈述文字和内容未经本站证实,本站对该文以及其中全部或者部分内容、文字的真实性、完整性、及时性,不作出任何保证或承若;
3.如本站转载稿涉及版权等问题,请作者及时联系本站,我们会及时处理。