The idea that the Excel solver "has a good reputation for being fast and 
accurate" does not withstand an examination  of the Excel solver's 
ability to solve the StRD nls test problems.  Solver's ability is 
abysmal.  13 of 27 "answers" have zero accurate digits, and three more 
have fewer than two accurate digits -- and this is after tuning the 
solver to get a good answer.  For details see

B. D. McCullough and Berry Wilson
"On the Accuracy of Statistical Procedures in Microsoft Excel 2000 and 
Excel XP,"
/Computational Statistics and Data Analysis/ *40*(4), 713-721, 2002

The situation is the same for Excel 2003 and Excel 2007.  The alleged 
"improvements" for Excel 2010 have had not much practical effect.  Excel 
solver does have the virture that it will always produce an answer, 
albeit one with zero accurate digits.

To see an extended example of precisely how solver fails:

B. D. McCullough
"Some Details of Nonlinear Estimation," Chapter Eight in
/Numerical Methods in Statistical Computing for the Social Sciences, /
Micah Altman, Jeff Gill and Michael P. McDonald, editors
New York: Wiley, 2004

I am unaware of R being applied to the StRD, but I did apply S+ to the 
StRD and, with analytic derivatives, it performed flawlessly.


On 02/19/2013 08:38 PM, r-help-request@r-project.org wrote:
> May I be allowed to say that the general comments on MS Excel may be alright,
> in this special case they are not.  The Excel Solver -- which is made by an
> external company, not MS -- has a good reputation for being fast and accurate.
> And it indeed solves least-squares and nonlinear problems better than some of
> the solvers available in R.
> There is a professional version of this solver, not available from Microsoft,
> that could be called excellent. We, and this includes me, should not be too
> arrogant towards the outside, non-R world, the 'barbarians' as the ancient
> Greeks called it.
>
> Hans Werner


-- 
B. D. McCullough, Professor
Department of Decision Sciences
LeBow College of Business

"So what's getting ubiquitous and cheap? Data. And what is
complementary to data? Analysis. So my recommendation is to
take lots of courses about how to manipulate and analyze
data: databases, machine learning, econometrics, statistics,
visualization, and so on." Google Chief Economist, Hal Varian,
New York Times, 25 February 2008


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