---
product_id: 6668213
title: "Introductory Time Series with R (Use R!)"
brand: "paul s.p. cowpertwaitandrew v. metcalfe"
price: "€ 45.13"
currency: EUR
in_stock: true
reviews_count: 13
url: https://www.desertcart.hr/products/6668213-introductory-time-series-with-r-use-r
store_origin: HR
region: Croatia
---

# Introductory Time Series with R (Use R!)

**Brand:** paul s.p. cowpertwaitandrew v. metcalfe
**Price:** € 45.13
**Availability:** ✅ In Stock

## Quick Answers

- **What is this?** Introductory Time Series with R (Use R!) by paul s.p. cowpertwaitandrew v. metcalfe
- **How much does it cost?** € 45.13 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.hr](https://www.desertcart.hr/products/6668213-introductory-time-series-with-r-use-r)

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## Description

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## Customer Reviews

### ⭐⭐⭐⭐⭐ 5.0 out of 5 stars







  
  
    Excellent and accessible introduction, suitable for all R users
  

*by S***E on Reviewed in the United States on December 9, 2012*

This is an excellent introduction to time series analysis in R, and is suitable for all readers who use R. In contrast to most statistics books, it does not presume an extensive mathematical background. Rather, it is a very much a progressive, didactic text, suitable for leisurely self-learning. The mathematics are presented briefly and appropriately for each topic, but progress and understanding do not depend on absorbing them in depth. It would be suitable, for instance, to social scientists, ecologists, public policy researchers, and so forth who use R.It is very much a multi-lesson tutorial on the basics of time series analysis, and should be worked through at the computer using R. The topics include decomposition (e.g., extracting seasonality vs. trends), handling autocorrelation, forecasting (e.g., the Bass model in marketing forecasts), regression models, and some more advanced topics such as spectral analysis. In some of the later topics, math is unavoidable and is presented when needed.There are two limitations to the book. First, as should be obvious from the preceding, some mathematicians and statisticians may be disappointed by the focus on tutorial rather than formal explanation. It has math but that's not the focus, so it would not be suitable for, say, a graduate-level mathematical stats course. Second, it of course cannot cover all aspects of time series analysis. It has examples from many domains (finance, operations, marketing, etc.) but limited depth in any single area; and it presents a variety of core models but does not cover the many advanced topics.Overall this is an excellent introduction to time series. If you're a general R analyst who wants to get started with time series, it's the best place to begin that I've seen.

### ⭐⭐⭐⭐⭐ 5.0 out of 5 stars







  
  
    What I hoped for
  

*by S***F on Reviewed in the United States on February 24, 2012*

Book is comprehensive but accessible to the non-statistician. Plenty of workable examples with simple code. Though not an R coding book, authors use pretty good coding practice and give some practical ideas for implementation. These guys clear up areas where I've previously struggled to get at the root of a method. In short, if you want to write TS proofs and academic papers, get another book. If you want to begin including more sophisticated TS models with your other work, this is the book for you.Only one knock, have been through several of the examples and there are some coding typos; nothing major but stay on your toes. Also, some of the algorithms may have changed since the book was written so you need to make use of the R help files to clear up any discrepancies with the author's work...some probably won't get cleared up because a more complex algorithm has been changed.This is a book I've been looking for.

### ⭐⭐⭐⭐ 4.0 out of 5 stars







  
  
    A good book
  

*by A***A on Reviewed in the United States on October 16, 2009*

A good book, although not presents a friendly and logical order to the subject. It has a good data set to students work throughout book. A summary of R code is shown at the end of chapters.Um bom livro para começar estudar séries temporais. Apesar de não ter uma sequência bem definida nos assuntos abordados, encontramos muito conteúdo no livro. Recomendável, principalmente por ser bem fácil obter o R a partir da internet, o que facilita o aprendizado quando não se dispõe de softwares consagrados, mas muito caros.

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*Product available on Desertcart Croatia*
*Store origin: HR*
*Last updated: 2026-05-17*