[R] A comment about R:

[Peter Muhlberger]

On 1/5/06 11:27 AM, "Achim Zeileis" <Achim.Zeileis at wu-wien.ac.at> wrote:

> As John and myself seem to have written our replies in parallel, hence
> I added some more clarifying remarks in this mail:
>> Note that the Anova() function, also in car, can more conveniently compute
>> Wald tests for certain kinds of hypotheses. More generally, however, I'd be
>> interested in your suggestions for an alternative method of specifying
>> linear hypotheses.
> My understanding was that Peter just wants to eliminate various elements
> from the terms(obj) which is what waldtest() in lmtest supports. If some
> other way of specifying nested models is required, I'd also be interested
> in that.


My two most immediate problems were a) to test whether a set of coefficients
were jointly zero (as Achim suggests, though the complication here is that
the varcov matrix is bootstrapped), but also b) to test whether the average
of a set of coefficients was equal to zero.  At other points in time, I
remember having had to test more complex linear hypotheses involving joint
combinations of equality, non-zero, and 'averages.'  The Stata interface for
linear hypothesis tests is amazingly straightforward.  For example, after a
regression, I could use the following to test the joint hypothesis that
v1=v2 and the average (or sum) of v3 through v5 is zero and .75v6+.25v7 is
zero:

test v1=v2
test v3+v4+v5=0, accum
test .75*v6+.25*v7=0, accum

I don't even have to set up a matrix for my test ];-) !  The output would
show not merely the joint test of all the hypotheses but the tests along the
way, one for each line of commands.  I vaguely remember the hypothesis
testing command after an ml run is much the same and cross-equation
hypothesis tests simply involve adding an equation indicator to the terms.
I can get huberized var-cov matrices simply by adding "robust" to the
regression command.  I believe there's also a command that will huberize a
var-cov matrix after the fact.  Subsequent hypothesis tests would be on the
huberized matrix.

I won't claim to know what's good for R or the R community, but it would be
nice for me and perhaps others if there were a comparable straightforward
command as in Stata that could meet a variety of needs.  I need to play w/
the commands that have been suggested to me by you guys recently, but I'm
looking at a multitude of commands none of which I suspect have the
flexibility and ease of use of the above Stata commands, at least for the
kind of applications I'd like.  Perhaps the point of R isn't to serve as a
package for a wider set of non-statisticians, but if it wishes to develop in
that direction, facilities like this may be helpful.  It's interesting that
Achim points out that a function John suggests is already available in R--an
indication that even R experts don't have a complete handle on everything in
R even on a relatively straightforward topic like hypothesis tests.

John is no doubt right that editorializing about statistics would be out of
place on an R help page.  But when I have gone to statistical papers, many
have been difficult to access & not very helpful for practical concerns.
I'm glad to hear that Long and Erwin's paper is helpful, but there's a
goodly list of papers mentioned in help.  Perhaps something that would be
useful is some way of highlighting on a help page which reference is most
helpful for practical concerns?

Again, thanks for all the great input from everyone!

Peter