Analysis of Integrated and Co-integrated Time Series with R (Use R) @ richardeward.com

Analysis of Integrated and Co-integrated Time Series with R (Use R)
by Bernhard Pfaff
from Springer

Features:

• Kindle Book

Customer Reviews:

• Avg. Customer Rating: 3.5 / 5.0

• Not much there.
  I'm not sure whether the author's purpose in writing this text book was to create a text on time series analysis or a manual for R users, but whichever it was, he didn't succeed. This is a very slim text (especially considering how much it costs), only 139 pages in total, and not surprisingly, there's just not that much in it. Pfaff covers a reasonably large range of topics, including stationary ARMA processes, cointegration, unit root tests, etc, but only a few pages are devoted to each topic and no worked... more info

• Excellent Short Book
  The UseR! series from Springer aims to be a series of short, focused books on implementation topics using the R statistical environment. Bernard Pfaff does a good job of presenting a good though brief overview that covers ARMA, stationarity, and cointegration. The math is not too heavy for the practitioner without a deep academic background, and the code examples are relevant and concise, demonstrating the concepts well. The book also does a reasonable job of integrating graphics into the analysis, which... more info

• a user manual for R
  A concise little book for a specialised audience. You might think of this as a user manual for R. It goes into some depth about how to apply R in analysis of time series data.
  The book also shows why R faces little competition from Mathematica or Maple. Those are general purpose maths packages. R is optimised for a narrow field. The graphics shown in the text are two dimensional plots of various types. Nothing flashy; no colour for instance. But perfectly adequate for the serious researcher.

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