I am new to using R and would appreciate some advice on which books to start with to get up to speed on using R. My Background: 1-C# programmer. 2-Programmed directly using IMSL (Now Visual Numerics). 3- Used in past SPSS and Statistica. I put together a list but would like to pick the "best of" and avoid redundancy. Any suggestions on these books would be helpful (i.e. too much overlap, porly written etc?) Books: 1-Analysis of Integrated and Co-integrated Time Series with R (Use R) - Bernhard Pfaff 2-An Introduction to R - W. N. Venables 3-Statistics: An Introduction using R - Michael J. Crawley 4-R Graphics (Computer Science and Data Analysis) - Paul Murrell 5-A Handbook of Statistical Analyses Using R - Brian S. Everitt 6-Introductory Statistics with R - Peter Dalgaard 7-Using R for Introductory Statistics - John Verzani 8-Data Analysis and Graphics Using R - John Maindonald; 9-Linear Models with R (Texts in Statistical Science) - Julian J. Faraway 10-Analysis of Financial Time Series (Wiley Series in Probability and Statistics)2nd edition - Ruey S. Tsay Thanks. Neil Gottlieb -------------------------------------------------------- This information is being sent at the recipient's request or with their specific understanding. The recipient acknowledges that by sending this information via electronic means, there is no absolute assurance that the information will be free from third party access, use, or further dissemination. This e-mail contains information that is privileged and/or confidential and may be subject to legal restrictions and penalties regarding its unauthorized disclosure or other use. You are prohibited from copying, distributing or otherwise using this information if you are not the intended recipient. Past performance is not necessarily indicative of future results. This is not an offer of or the solicitation for any security which will be made only by private placement memorandum that may be obtained from the applicable hedge fund. If you have received this e-mail in error, please notify us immediately by return e-mail and delete this e-mail and all attachments from your system. Thank You.
ngottlieb at marinercapital.com a ?crit :> I am new to using R and would appreciate some advice on > which books to start with to get up to speed on using R. > > My Background: > 1-C# programmer. > 2-Programmed directly using IMSL (Now Visual Numerics). > 3- Used in past SPSS and Statistica. > > I put together a list but would like to pick the "best of" > and avoid redundancy. > > Any suggestions on these books would be helpful (i.e. too much overlap, > porly written etc?) > > Books: > 1-Analysis of Integrated and Co-integrated Time Series with R (Use R) - > Bernhard Pfaff > 2-An Introduction to R - W. N. Venables > 3-Statistics: An Introduction using R - Michael J. Crawley > 4-R Graphics (Computer Science and Data Analysis) - Paul Murrell > 5-A Handbook of Statistical Analyses Using R - Brian S. Everitt > 6-Introductory Statistics with R - Peter Dalgaard > 7-Using R for Introductory Statistics - John Verzani > 8-Data Analysis and Graphics Using R - John Maindonald; > 9-Linear Models with R (Texts in Statistical Science) - Julian J. > Faraway > 10-Analysis of Financial Time Series (Wiley Series in Probability and > Statistics)2nd edition - Ruey S. Tsay > > Thanks. > > Neil Gottlieb >Neil, I am also new to R and I just bought the book of Peter Dalgaard (n?6). I find it very practical. It covers a large panel of principal statistical techniques that you can use directly. I thinkk it is a good start for a R beginner. At least, it is good for me! Don't forget the many resources on the R website. Regards. -- Alain Reymond CEIA Bd Saint-Michel 119 1040 Bruxelles Tel: +32 2 736 04 58 Fax: +32 2 736 58 02 alain.reymond at ceia.com PGPId : 0xEFB06E2E
Alain, Can you tell us what you plan to use R for? Regards, -Cody ngottlieb@marinercapital.com a écrit :> I am new to using R and would appreciate some advice on > which books to start with to get up to speed on using R. > > My Background: > 1-C# programmer. > 2-Programmed directly using IMSL (Now Visual Numerics). > 3- Used in past SPSS and Statistica. > > I put together a list but would like to pick the "best of" > and avoid redundancy. > > Any suggestions on these books would be helpful (i.e. too much overlap, > porly written etc?) > > Books: > 1-Analysis of Integrated and Co-integrated Time Series with R (Use R) - > Bernhard Pfaff > 2-An Introduction to R - W. N. Venables > 3-Statistics: An Introduction using R - Michael J. Crawley > 4-R Graphics (Computer Science and Data Analysis) - Paul Murrell > 5-A Handbook of Statistical Analyses Using R - Brian S. Everitt > 6-Introductory Statistics with R - Peter Dalgaard > 7-Using R for Introductory Statistics - John Verzani > 8-Data Analysis and Graphics Using R - John Maindonald; > 9-Linear Models with R (Texts in Statistical Science) - Julian J. > Faraway > 10-Analysis of Financial Time Series (Wiley Series in Probability and > Statistics)2nd edition - Ruey S. Tsay > > Thanks. > > Neil Gottlieb >Cody Hamilton, PhD Edwards Lifesciences [[alternative HTML version deleted]]
Hi, ngottlieb at marinercapital.com wrote:> I am new to using R and would appreciate some advice on > which books to start with to get up to speed on using R. > > My Background: > 1-C# programmer. > 2-Programmed directly using IMSL (Now Visual Numerics). > 3- Used in past SPSS and Statistica. > > I put together a list but would like to pick the "best of" > and avoid redundancy. > > Any suggestions on these books would be helpful (i.e. too much overlap, > porly written etc?) > > Books: > 1-Analysis of Integrated and Co-integrated Time Series with R (Use R) - > Bernhard Pfaff > 2-An Introduction to R - W. N. Venables > 3-Statistics: An Introduction using R - Michael J. Crawley > 4-R Graphics (Computer Science and Data Analysis) - Paul Murrell > 5-A Handbook of Statistical Analyses Using R - Brian S. Everitt > 6-Introductory Statistics with R - Peter Dalgaard > 7-Using R for Introductory Statistics - John Verzani > 8-Data Analysis and Graphics Using R - John Maindonald; > 9-Linear Models with R (Texts in Statistical Science) - Julian J. > Faraway > 10-Analysis of Financial Time Series (Wiley Series in Probability and > Statistics)2nd edition - Ruey S. Tsayas one other message says, it depends a lot on your ideas what you want to do with R. And, I'd like to add, how familiar you are with statistics. One book I am missing in your list is Venables / Ripley: Modern Applied Statistics with S. I can highly recommend it. If you are going to buy yourself only one book, then I would say: buy Venables/Ripley Best, Roland
There are some online sources that you might find useful. You could
get started on those while you decide what books to get:
- CRAN contributed documentation
http://cran.r-project.org/other-docs.html
- S Poetry
http://www.burns-stat.com/pages/spoetry.html
- Zoonekynd book
http://zoonek2.free.fr/UNIX/48_R/all.html
- R manuals
http://cran.r-project.org/manuals.html
- R News
http://cran.r-project.org/doc/Rnews/
- various packages have vignettes which are PDF documents that discuss the
package, often at length.
vignette() # shows vignettes for installed packages
- there was a vignette browser posted to r-devel recently
http://tolstoy.newcastle.edu.au/R/e2/devel/07/06/3498.html
On 6/12/07, ngottlieb at marinercapital.com <ngottlieb at
marinercapital.com> wrote:> I am new to using R and would appreciate some advice on
> which books to start with to get up to speed on using R.
>
> My Background:
> 1-C# programmer.
> 2-Programmed directly using IMSL (Now Visual Numerics).
> 3- Used in past SPSS and Statistica.
>
> I put together a list but would like to pick the "best of"
> and avoid redundancy.
>
> Any suggestions on these books would be helpful (i.e. too much overlap,
> porly written etc?)
>
> Books:
> 1-Analysis of Integrated and Co-integrated Time Series with R (Use R) -
> Bernhard Pfaff
> 2-An Introduction to R - W. N. Venables
> 3-Statistics: An Introduction using R - Michael J. Crawley
> 4-R Graphics (Computer Science and Data Analysis) - Paul Murrell
> 5-A Handbook of Statistical Analyses Using R - Brian S. Everitt
> 6-Introductory Statistics with R - Peter Dalgaard
> 7-Using R for Introductory Statistics - John Verzani
> 8-Data Analysis and Graphics Using R - John Maindonald;
> 9-Linear Models with R (Texts in Statistical Science) - Julian J.
> Faraway
> 10-Analysis of Financial Time Series (Wiley Series in Probability and
> Statistics)2nd edition - Ruey S. Tsay
>
> Thanks.
>
> Neil Gottlieb
Pat: I have done PCA to extract eigenvectors on return series for equities. Rotation does help and does make factors more understandable, have had success doing this. You are right, when doing pure statistical factors, one tends to find first factor which explains most of the variance is the Market Beta. Our scree score showed 20 factors explains most of the variance in equity returns. If you sort on the factor loadings, the other first few factors tend to things such as interest rates,Energy prices, currency exposure. After that it gets a little more complicated what the factors are but they tend to be sector specific. That's the major complaint about pure statistical factor analysis... Interpretation but can get reasonable idea by sorting factor cores. As for missing values, a lot of work has been done there with sampling such as EM and Maximum Likehood. I will check out your R code. Hopefully it will get included Eventually in the Portfolio package. Being new to R, will need to figure out how to "source" the code to R! Regards, Neil -----Original Message----- From: Patrick Burns [mailto:patrick at burns-stat.com] Sent: Wednesday, June 13, 2007 12:56 PM To: Gottlieb, Neil Subject: Re: [R] R Book Advice Needed Neil, 'factor.model.stat' is a part of POP, which is an R package (that runs under S-PLUS as well). We've made 'factor.model.stat' public domain so you don't have to have POP in order to use it. The version of 'factor.model.stat' in the Public Domain area is not in a package. You can just 'source' the code. I just checked and 'factor.model.stat' is not in the 'portfolio' package -- I'm not sure why they haven't included it. The statistical factors are already orthogonal. Rotation is only aimed at trying to make them more interpretable. I'm not very optimistic about that, other than the first factor represents the market. But if you do have success, I'd be interested in hearing of it. A caveat to the paragraph above is that orthogonality assumes no missing values. Having no missing values is not a very common occurrence though (at least for a lot of us). Most of the code in 'factor.model.stat' is handling missing values. I haven't had call for rotations, but I'd be extremely surprised if there weren't a bunch somewhere in R. The 'RSiteSearch' function should be your friend for this. Pat ngottlieb at marinercapital.com wrote:>Thank Patrick. Is factor.model.stat part of r packages? > >Also want to rotate the factors so they are orthogonal. >Do you have varimax or promax rotation functio? > >Neil > >-----Original Message----- >From: Patrick Burns [mailto:patrick at burns-stat.com] >Sent: Wednesday, June 13, 2007 11:28 AM >To: Gottlieb, Neil >Subject: Re: [R] R Book Advice Needed > >Most or all of the work for your factor model should be done in 'factor.model.stat' from the Public Domain page of the Burns Statistics website. It is also in the 'portfolio' package, I believe. > >Patrick Burns >patrick at burns-stat.com >+44 (0)20 8525 0696 >http://www.burns-stat.com >(home of S Poetry and "A Guide for the Unwilling S User") > >ngottlieb at marinercapital.com wrote: > > > >>Cody: >> >>Think you might have asked the question for me Neil. >> >>I do time series analysis of return data in finance. >> >>I will be creating a factor model based on PCA Or Single Value >>Decomposition to get Eigenvectors Of the correlation matrix (tends to >>work better for finance data Than covariance). >> >>>From there will be doing style analysis, some optimization, >>Regime switching, co-intregration testing and some Statistical Process >>Control charting such as CUSUM. >> >>Ultimately, what I learned over the years with statistics, >>visualization is critical for my end-users. The don't care what >>cluster method I use, be it Hierarchical or Rosseau' newer methods >>such as Fanny, which I find more robust. >> >>In end I need practical stuff: as a programmer on Data types, data >>structures and even how to format and read in Data. >> >>So that's basically stuff I will be doing. >> >>Neil >> >>-----Original Message----- >>From: r-help-bounces at stat.math.ethz.ch >>[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of >>Cody_Hamilton at edwards.com >>Sent: Tuesday, June 12, 2007 6:36 PM >>To: r-help at stat.math.ethz.ch >>Subject: Re: [R] R Book Advice Needed >> >> >> >>Alain, >> >>Can you tell us what you plan to use R for? >> >>Regards, >>-Cody >> >>ngottlieb at marinercapital.com a ?crit : >> >> >> >> >>>I am new to using R and would appreciate some advice on which books >>>to start with to get up to speed on using R. >>> >>>My Background: >>>1-C# programmer. >>>2-Programmed directly using IMSL (Now Visual Numerics). >>>3- Used in past SPSS and Statistica. >>> >>>I put together a list but would like to pick the "best of" >>>and avoid redundancy. >>> >>>Any suggestions on these books would be helpful (i.e. too much >>>overlap, porly written etc?) >>> >>>Books: >>>1-Analysis of Integrated and Co-integrated Time Series with R (Use R) >>>- Bernhard Pfaff 2-An Introduction to R - W. N. Venables >>>3-Statistics: An Introduction using R - Michael J. Crawley 4-R >>>Graphics (Computer Science and Data Analysis) - Paul Murrell 5-A >>>Handbook of Statistical Analyses Using R - Brian S. Everitt >>>6-Introductory Statistics with R - Peter Dalgaard 7-Using R for >>>Introductory Statistics - John Verzani 8-Data Analysis and Graphics >>>Using R - John Maindonald; 9-Linear Models with R (Texts in >>>Statistical Science) - Julian J. >>>Faraway >>>10-Analysis of Financial Time Series (Wiley Series in Probability and >>>Statistics)2nd edition - Ruey S. Tsay >>> >>>Thanks. >>> >>>Neil Gottlieb >>> >>> >>> >>> >>> >>Cody Hamilton, PhD >>Edwards Lifesciences >> [[alternative HTML version deleted]] >>-------------------------------------------------------- >> >> >> >>This information is being sent at the recipient's request >>or...{{dropped}} >> >>______________________________________________ >>R-help at stat.math.ethz.ch mailing list >>https://stat.ethz.ch/mailman/listinfo/r-help >>PLEASE do read the posting guide >>http://www.R-project.org/posting-guide.html >>and provide commented, minimal, self-contained, reproducible code. >> >> >> >> >> >> > > > >-------------------------------------------------------- This information is being sent at the recipient's request or...{{dropped}}