Hello Jambunathan, The ODT version was prepared "by hand" using LibreOffice. This was written (last May) before your org-odt functions became part of org-mode (if I'm right). I would now also do it with org-mode.
Christophe Jambunathan K <kjambunat...@gmail.com> writes: > Christophe > > I see an ODT file in there - LFPdetection_in.odt > http://hal.archives-ouvertes.fr/hal-00591455/ > > May I ask how the document was produced. > > Do you have any insights on how the Org's ODT exporter performs wrt your > input Org file. Just curious. > >> @article{Delescluse2011, >> title = "Making neurophysiological data analysis reproducible: Why and how?", >> journal = "Journal of Physiology-Paris", >> volume = "", >> number = "0", >> pages = " - ", >> year = "2011", >> note = "", >> issn = "0928-4257", >> doi = "10.1016/j.jphysparis.2011.09.011", >> url = "http://www.sciencedirect.com/science/article/pii/S0928425711000374";, >> author = "Matthieu Delescluse and Romain Franconville and Sébastien Joucla >> and Tiffany Lieury and Christophe Pouzat", >> keywords = "Software", >> keywords = "R", >> keywords = "Emacs", >> keywords = "Matlab", >> keywords = "Octave", >> keywords = "LATEX", >> keywords = "Org-mode", >> keywords = "Python", >> abstract = "Reproducible data analysis is an approach aiming at >> complementing classical printed scientific articles with everything required >> to independently reproduce the results they present. “Everything” covers >> here: the data, the computer codes and a precise description of how the code >> was applied to the data. A brief history of this approach is presented >> first, starting with what economists have been calling replication since the >> early eighties to end with what is now called reproducible research in >> computational data analysis oriented fields like statistics and signal >> processing. Since efficient tools are instrumental for a routine >> implementation of these approaches, a description of some of the available >> ones is presented next. A toy example demonstrates then the use of two open >> source software programs for reproducible data analysis: the “Sweave family” >> and the org-mode of emacs. The former is bound to R while the latter can be >> used with R, Matlab, Python and many more “generalist” data processing >> software. Both solutions can be used with Unix-like, Windows and Mac >> families of operating systems. It is argued that neuroscientists could >> communicate much more efficiently their results by adopting the reproducible >> research paradigm from their lab books all the way to their articles, thesis >> and books." >> } -- Most people are not natural-born statisticians. Left to our own devices we are not very good at picking out patterns from a sea of noisy data. To put it another way, we are all too good at picking out non-existent patterns that happen to suit our purposes. Bradley Efron & Robert Tibshirani (1993) An Introduction to the Bootstrap -- Christophe Pouzat MAP5 - Mathématiques Appliquées à Paris 5 CNRS UMR 8145 45, rue des Saints-Pères 75006 PARIS France tel: +33142863828 mobile: +33662941034 web: http://www.biomedicale.univ-paris5.fr/physcerv/C_Pouzat.html
