Applied Time Series Analysis with R

Released on by Wayne A. Woodward
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  • Applied Time Series Analysis with R Book Detail

  • Author : Wayne A. Woodward
  • Release Date : 2017-02-17
  • Publisher : CRC Press
  • Genre : Mathematics
  • Pages : 460
  • ISBN 13 : 1498734316
  • File Size : 21,21 MB
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Applied Time Series Analysis with R by Wayne A. Woodward PDF Summary

Book Description: 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" Provides the R package tswge available on CRAN which contains functions and over 100 real and simulated data sets to accompany the book. Extensive help regarding the use of tswge functions is provided in appendices and on an associated website. 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).

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Applied Time Series Analysis with R

Applied Time Series Analysis with R

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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 ra

Applied Time Series Analysis

Applied Time Series Analysis

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Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines.

Applied Time Series Analysis

Applied Time Series Analysis

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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 r

Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R

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Build efficient forecasting models using traditional time series models and machine learning algorithms. Key FeaturesPerform time series analysis and forecastin