Re: How to have correct citation of gnumeric

Ken, I think Gabriela is asking how Gnumeric should be credited in the
paper they are publishing.


On 29 January 2016 at 10:59, ken <gebser mousecar com> wrote:
On 01/28/2016 11:33 AM, Gabriela Hoff wrote:

Dear Sir or Madam

I am using R statisitcal tookit and Gnumeric to perform statistical
analysis to a paper and I would like to have the correct citation to
gnumeric in this paper.
I am using the statistical package of the last gnumeric version available.

To R I was able to retrieve the infomration:
"[31] R Core Team. R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria. URL (2014)."

I tried to find information in the webpage but I didn't succeed.
Would you, please, send me the directions to find the correct citation?

Thank you in advance,
Gabriela Hoff
Dra. Biociência Nucleares - Física Médica
Fone: 51 83333588


I don't understand what sort of citation you're seeking or what that
citation is meant to verify or support.  Perhaps you could explain this

In the off-chance it might be helpful, here's the entry for R-core included
in the RPM package:

$ rpm -qi R-core
Name        : R-core                       Relocations: (not relocatable)
Version     : 3.2.3                             Vendor: Fedora Project
Release     : 1.el5                         Build Date: Fri 11 Dec 2015
09:19:43 PM EST
Install Date: Wed 06 Jan 2016 09:37:28 AM EST      Build Host:
Group       : Applications/Engineering      Source RPM:
Size        : 84421779                         License: GPLv2+
Signature   : DSA/SHA1, Tue 15 Dec 2015 04:30:09 AM EST, Key ID
Packager    : Fedora Project
URL         :
Summary     : The minimal R components necessary for a functional runtime
Description :
A language and environment for statistical computing and graphics.
R is similar to the award-winning S system, which was developed at
Bell Laboratories by John Chambers et al. It provides a wide
variety of statistical and graphical techniques (linear and
nonlinear modelling, statistical tests, time series analysis,
classification, clustering, ...).

R is designed as a true computer language with control-flow
constructions for iteration and alternation, and it allows users to
add additional functionality by defining new functions. For
computationally intensive tasks, C, C++ and Fortran code can be linked
and called at run time.


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