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R codes for numerical analysis methods

3 messages · Steven Stoline, Dennis Murphy, Mauricio Zambrano-Bigiarini

Original
Steven Stoline
# 
Dear All:

I am wondering if I can find R codes (functions) for numerical analysis
methods, linear algebra, and differential equations available somewhere.

many thanks
steve

------------------------
Steven M. Stoline
1123 Forest Avenue
Portland, ME 04112
sstoline at gmail.com
Dennis Murphy
# 
Hi:

1. Victor Bloomfield's book "Using R for Numerical Analysis in Science
and Engineering", published by CRC Press/Chapman and Hall. Links to
the code found at the book's web site:
http://www.crcpress.com/product/isbn/9781439884485
This book covers optimization and diff eqs in some detail.

2. John Monahan's book "Numerical Methods of Statistics" (Cambridge).
R code for the second edition can be found at the author's web site:
http://www4.stat.ncsu.edu/~monahan/nmos2/toc.html

3. Several good courses re statistical computing in R exist on-line.
Monahan has one; two others that come to mind are Galin Jones' course
at the University of Minnesota (STAT 8701) and Robert Gray's course at
Harvard (BIO 248).
http://biowww.dfci.harvard.edu/~gray/248-02/Welcome.html
Gray's course used S-PLUS (it was in 2002) but most of the code should
be translatable to R.

 I am certain to have missed several good stat computing courses;
perhaps others can chime in with suggestions. Google should be a
friend here.

4. Soetaert et al.'s book "Solving Differential Equations in R" (Springer):
http://www.springer.com/statistics/computational+statistics/book/978-3-642-28069-6
and a paper of the same name in the R Journal:
http://journal.r-project.org/archive/2010-2/RJournal_2010-2_Soetaert~et~al.pdf
The book code is accessible by clicking the box labeled
"Extras:Springer.com" under the tabl "Additional Information".

5. The Matrix package should be helpful in concert with notes/text on
numerical linear algebra if the above sources are insufficient. See
the vignette for its capabilities.

Hopefully that should be sufficient to get you started...this is by no
means a comprehensive list.

Dennis
On Sun, Oct 12, 2014 at 7:31 AM, Steven Stoline <sstoline at gmail.com> wrote:
Mauricio Zambrano-Bigiarini
#
On 12/10/14 11:31, Steven Stoline wrote:
Hi Steve,

Regarding differential equations, and in addition to all the material 
listed by Dennis, I would start looking at the CRAN Task View: 
Differential Equations:

http://cran.r-project.org/web/views/DifferentialEquations.html

IHTH,

Mauricio Zambrano-Bigiarini, PhD