[Newbie] Row-Iterator for data.frame??

hello all,

for my diploma-thesis i want to statitically analyze near-infrared-spectra.
a spectrum is given by the y-values of 1038 equi-distant x-points.
in nature, a spectrum is a continuous curve. for analysis, every x-point
is seen as a statistical variable.

now my problem:
first, i read a csv-table in a data.frame called sTable via read.table.

besides some meta-data there are 1038 variables holding absorbance-values
for each wave-number, so a spectrum can be seen as a "case". 

when i calculate e.g. means for every variable, R works very *fast*. also
if i want to scale a variable for every spectrum (=case) it's fast: sTable$WN4000
<- sTable$WN4000 / 1.34 .
but for some reasons i have to iterate through the spectra, especially when
i want to differentiate a curve, because then i first have to build a interpolation
polynom from the given x-points and y-values of a specific case.

i wrote a function getCase <- function( dataFrame, caseNo) with return-value
of type data.frame and holding the case "caseNo" of the dataFrame. 

now, this results in absolutely bad performance. 

my question: 
what is the most convenient and fastest way to access a single row of a
data.frame? if possible, i'd like something i could use like this:
sTable <- getSpectraTable()
case11 <- getRow( sTable, 11)
wn4000 <- case11$WN4000
is there a built-in function/method in R i didn't find yet?
also i'd like to avoid casting the data.frame to a matrix (or whatever)
for reducing the risks by holding data redundantly.

thank you for your help!
till





________________________________________
Der clevere Infobote - Shopping-Tipps bequem abonniert. Jetzt neu bei http://www.epost.de


-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._