[R] A comment about R:
nassar at noos.fr
Thu Jan 5 12:59:40 CET 2006
Roger thanks for the reproduction.
As a user of Stata & R, for common analysis I do use Stata and often, I have
to adapt some computations or to do some complex hierarchical modeling and
then I switch to R.
For me switching from Stata (or other statistical software, SO) to R (or
other statistical language) requests a double effort:
- Programming (laziness?) : writing and testing the code; considering the
data as N array or any data frame in order to optimize performance
- Statistical testing : I test the model over a simulated data set and
validate that the statistical process is giving me back the adequate
parameter estimates. An additional step one doesn't need when using an
For me using Stata (or any other SO), has the advantage of using a high
quality code written & tested by an organization & their clients.
Getting back to Roger replication, I find such replication very useful.
Test whether the R-code is giving back adequate results. So it's a very good
starting point before adapting the R-code to one's needs.
Stata advantage : one can download additional ado files ('package' like) and
with the permission of the author, adapt them or translate them into R-code.
Not only R &Stata are good products, they also show a valuable asset : the
Happy new year
Le 5/01/06 10:46, « Robert Chung » <rechung at gmail.com> a écrit :
> Roger Bivand wrote:
>> Gabor Grothendieck wrote:
>>> For example, consider this introductory session in Stata:
>> Could I ask for comments on:
>> source(url("http://spatial.nhh.no/R/etc/capabilities.R"), echo=TRUE)
>> as a reproduction of the Stata capabilities session?
> Roger, I think your reproduction of the Stata session is excellent.
> However, in a deeper sense, perhaps it's *too* faithful a replication. I
> don't normally do analyses exactly the same way in R and in Stata, so
> although it's possible to contort R into producing Stata-like output, why
> would anyone want to? For example, in the sample Stata session, they run a
> t-test before plotting any data. In R, I'd tend to plot early and test
> hypotheses after. Rather that print out the top and bottom 5 mileage cars,
> I might plot(weight,mpg,col=as.integer(foreign)) and identify() the
> bivariate oddities. Rather than start into linear models, I might do some
> lowess() lines. I'd probably do a splom() pretty early. Depending on what
> I was doing, maybe I'd do something like
> Stata and R are both fine products, but I sometimes wonder how the tools
> one chooses affect the analyses one does.
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
More information about the R-help