--- product_id: 6668213 title: "Introductory Time Series with R (Use R!)" price: "COP 449037" currency: COP in_stock: true reviews_count: 13 url: https://www.desertcart.co/products/6668213-introductory-time-series-with-r-use-r store_origin: CO region: Colombia --- # Introductory Time Series with R (Use R!) **Price:** COP 449037 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Introductory Time Series with R (Use R!) - **How much does it cost?** COP 449037 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.co](https://www.desertcart.co/products/6668213-introductory-time-series-with-r-use-r) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research. Review: Excellent and accessible introduction, suitable for all R users - 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. Review: What I hoped for - 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. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | #379,574 in Books ( See Top 100 in Books ) #23 in Signal Processing #40 in Econometrics & Statistics #64 in Mathematical & Statistical Software | | Customer Reviews | 4.1 out of 5 stars 73 Reviews | ## Images ![Introductory Time Series with R (Use R!) - Image 1](https://m.media-amazon.com/images/I/513AKChOaHL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ Excellent and accessible introduction, suitable for all R users *by S***R 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. ### ⭐⭐⭐⭐⭐ What I hoped for *by S***F 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. ### ⭐⭐⭐⭐ A good book *by A***A 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. --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.co/products/6668213-introductory-time-series-with-r-use-r](https://www.desertcart.co/products/6668213-introductory-time-series-with-r-use-r) --- *Product available on Desertcart Colombia* *Store origin: CO* *Last updated: 2026-08-06*