From: Liaw, Andy <andy_liaw_at_merck.com>

Date: Tue 24 Jan 2006 - 07:33:06 EST

R-help@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 Received on Tue Jan 24 07:50:22 2006

Date: Tue 24 Jan 2006 - 07:33:06 EST

Thomas Lumley has some notes that might be very helpful for you:

http://faculty.washington.edu/tlumley/Rcourse/

Deepayan Sarkar also has some notes that might be of interest:

http://www.cs.wisc.edu/~deepayan/SIBS2005/

Andy

From: Baronin P. Storch von

*>
**>
*

> Dear R-wizards!

*>
**> I have been learning on my own how to use this fantastic
**> program.. but I agree with some people that even with the
**> manuals, the faq and so on.. when you are sitting fully
**> alone.. progress can be ... slow... very slow indeed.. In
**> fact sometimes, looking at the "solutions" provided by some
**> of you- I am just flabbergasted to the point that I couldn't
**> figure out how to come up with them myself (sometimes I don't
**> even understand them :-( )
**>
**> But after spending around three weeks on this, and starting
**> to get fairly obsessed with it, I decided I shall ask for
**> help,'cause i can't figure out in the documentation where I
**> should look for this.
**>
**> In Maple when I want to automatize something boring I write a
**> procedure..
**> here I am not too sure.. how to bind together a few
**> statements- most of which are functions... sounds like it
**> would make up a personnal macro..
**> I am sure I am doing things in such a primitive way that the
**> R-specialists will wince.. but that's how it goes with beginners!
**>
**> Set up.
**>
**> I have 4 fairly large data base with unequal number of lines
**> (around 1200-1500), but identical number of columns (162)-years.
**>
**> for each column, I construct a data-frame with the
**> corresponding column of DB1, then from DB2, .. DB4.
**>
**> This yields a data.frame in which many data are NA- some are
**> real NAs some others are because I have to take the max of
**> the lines. In any case, the number of NAs of each of these 4
**> columns is not identical.
**>
**> I extract (by sorting and creating 4 new vectors) 4 vectors
**> of variable length
**> -the relevant and interesting data- to whom I wish to apply
**> some standardized treatment: that is normality with say
**> Shapiro-Wilks, Levene, etc.. Kruskal-Wallis and probably
**> other things..
**>
**> I am not showing my tasks because I do not think that I want
**> to bother the readers with this,, rather ask for general
**> remarks ( you can provide examples of your own).
**>
**> For each column I want to write the results in a table.. and
**> append these resulta for each column.
**>
**> I was fairly efficient at doing that for a particular column,
**>
**> but then the simple thought of apply this "list of tasks"
**> 162 times.. makes me..
**> feel that there should be a way.... to speed up my
**> execution.. (a loop)
**>
**> However I have not been able to create a super "function" (or
**> procedure) that could tie all these statements together in a
**> sensible fashion.. because each time the data.frame created
**> is generated by a function.. and somehow i still did not
**> figure out how to write a function of functions
**> and then maybe a loop do for all values of dates =1:162 this
**> function..
**>
**> (all the stuff I tried failed, because I was indexing objects
**> that were also indexed.. I am vague.. but then retracing a 3
**> weeks of trials and errors errors errors errors ...\infty :-)
**> is cumbersome)
**>
**>
**> 1. Could anybody give me suggestions where to look and maybe
**> unveil the tricks of the function of functions ..
**>
**> ideally I would construct a loop executing a super function..
**> whose results would be dumped in a file (write.table)
**> appending each time the result of the loop i..
**>
**> but I was not able to construct that...
**> should I make a wiser use of these "apply, tapply, sapply"
**> marvels? I dunno.
**> does something like for (i in 1:G){sapply(b(i),sw)} were
**> b(i) is the dataframe for column i, and SW is a function
**> (super function-procedure) make sense in R?
**>
**> I see that there are some fully esoterical paragraphs on
**> things that seem to be relevant in the manuals.. but..
**> esoterical.. I cannot make sense of them... vicious circle..
**>
**>
**> Thank you in advance for any courageous that would give me a hint..
**>
**> Christina
**>
**> ______________________________________________
**> R-help@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
**>
**>
*

R-help@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 Received on Tue Jan 24 07:50:22 2006

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