[This was also posted to the same question on sci.stat.consult]

On 25 May 2004 15:44:34 -0700, [EMAIL PROTECTED] (Xinmiao)
wrote:

> Hi,
> 
> I have the following question: If one is limited by the number of
> total data points (# sampling points * # replicates), then in order to
> get a good curve fitting, which is more preferable - to have fewer
> sampling points and more replicates at each point, or to have more
> sampling points and fewer replicates? I suspect that it is the latter,
> but I don't know any statistical reference or background for that. Can
> someone please kindly help me out here?

I'm sure that the answer depends on the error-of-measurement
or "replication error."  If a replication is going to give you 
exactly the same value as the first measurement, then there
is little to gain in making second measurements.  If it is 
different:  Does a "replication" imply a set of points, or whole
curve?  - that is, does the experiment generate time-series.


However, I recognize the problem from something concerning
repeated measures.  Power analysis there ends up being awkward 
because you seldom have good knowledge of all the variance terms.

 - maybe this Reply will be a head-start for someone who knows the 
problem for fitting curves.  However, I wonder if the question is too
comprehensive.   "Curve-fitting"  seems to me to be approximately
as broad as "fitting some kind of linear or non-linear regression."


-- 
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
.
.
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