Introductory Time Series With R

Author: Paul S.P. Cowpertwait
Publisher: Springer Science & Business Media
ISBN: 0387886982
Size: 42.60 MB
Format: PDF, ePub, Mobi
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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.

Mastering Predictive Analytics With R

Author: Rui Miguel Forte
Publisher: Packt Publishing Ltd
ISBN: 1783982810
Size: 58.37 MB
Format: PDF
View: 5827
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For MA processes, and indeed all the time series models discussed in this
chapter, there are a number of very useful references with examples in R. An
excellent text from the Use R! series of Springer is Introductory Time Series by
Cowpertwait and Metcalfe. We also recommend Time Series Analysis With
Applications in R, Cryer and Chan, Springer. In R, we can simulate MA processes
(among others) using the arima.sim() function. This is actually a general function
that we will use ...

Political Analysis Using R

Author: James E. Monogan III
Publisher: Springer
ISBN: 3319234463
Size: 58.81 MB
Format: PDF
View: 4319
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Alvarez RM, Levin I, Pomares J, Leiras M (2013) Voting made safe and easy: the
impact of e-voting on citizen perceptions. Polit Sci Res Methods 1(1):117–137
Bates D, Maechler M, Bolker B, Walker S (2014) lme4: linear mixed-effects
models using Eigen and S4. R package version 1.1-7. http://www.CRAN.R-
project.org/package=lme4 Becker RA, Cleveland WS, Shyu M-J (1996) The
visual design and control of Trellis display. J Comput Graph Stat 5(2):123–155
Beniger JR, Robyn DL ...

Time Series Analysis And Its Applications

Author: Robert H. Shumway
Publisher: Springer
ISBN: 9783319524511
Size: 80.14 MB
Format: PDF, Docs
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This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series.

R Data Visualization Cookbook

Author: Atmajitsinh Gohil
Publisher: Packt Publishing Ltd
ISBN: 1783989513
Size: 72.75 MB
Format: PDF, Mobi
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It is not possible to cover the topic of time series analysis in detail and I would
highly recommend readers to refer to Introductory Time Series with R given in the
See also section. In this recipe, we will explore a simple additive decomposition
model. The model is represented as follows: Xt = Mt+St+Zt In this notation, the
variables at time t are as follows: f Xt: This is an observed series f Mt: This is the
trend f St: This is the seasonal effect f Zt: This is the error term It is also possible to
use a ...

Applied Time Series Analysis With R Second Edition

Author: Wayne A. Woodward
Publisher: CRC Press
ISBN: 1498734316
Size: 35.26 MB
Format: PDF, ePub
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We continue to believe that this book is a one-of-a-kind book for teaching
introductory time series. We make every effort to not only present a compendium
of models and methods supplemented by a few examples along the way. Instead,
we dedicate extensive coverage designed to provide insight into the models, we
discuss features of realizations from various models, and we give caveats
regarding the use and interpretation of results based on the models. We have
used the book ...

Introductory Statistics With R

Author: Peter Dalgaard
Publisher: Springer Science & Business Media
ISBN: 9780387790534
Size: 66.88 MB
Format: PDF, ePub
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Software for Data Analysis Programming with R John M. Chambers This book
guides the reader through programming with R, beginning with simple interactive
use and progressing by gradual stages, starting with simple functions. ... 510 pp. (
Statistics and Computing) Hardcover ISBN 978-0-387-75935-7 Time Series
Analysis with Applications in R Jonathan D. Cryer and Kung-Sik Chan Time
Series Analysis With Applications in R, Second Ed., presents an accessible
approach to ...

An Introduction To Analysis Of Financial Data With R

Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1119013461
Size: 55.85 MB
Format: PDF, Kindle
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The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.

Modeling Techniques In Predictive Analytics With Python And R

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 013389214X
Size: 35.17 MB
Format: PDF
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Introductory Time Series with R. New York: Springer. Cox, D. R. 1958. Planning
of Experiments. New York: Wiley. Cox, D. R. 1970. Analysis of Binary Data.
London: Chapman and Hall. Cox, T. F. and M. A. A. Cox 1994. Multidimensional
Scaling. London: Chapman & Hall. 296 Craddock, J. (ed.) 2012. VideoHound's
Golden Movie Retriever 2013: The Complete Guide to Movies on All Home
Entertainment Formats. Farmington Hills, Mich.: Gale. Cranor, L. F. and B. A.
LaMacchia 1998.

Analysis Of Integrated And Cointegrated Time Series With R

Author: Bernhard Pfaff
Publisher: Springer Science & Business Media
ISBN: 0387759670
Size: 54.96 MB
Format: PDF, ePub, Mobi
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Time Series Analysis With Applications in R, Second Ed., presents 2008. 2nd Ed.,
494 pp. (Springer Texts in Statistics) Hardcover ISBN 0-387-75958-6 Time Series
Analysis and Its Applications with R Examples Robert H. Shumway and David S.
Stoffer This book presents a balanced and comprehensive treatment of both time
and frequency domain methods with accompanying theory. Numerous examples
using non-trivial data illustrate solutions to problems such as evaluating pain ...