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From: Matthias Schabel (boost_at_[hidden])
Date: 2006-12-07 17:01:02

>> As far as I can see, precision needs to be the same type as the
>> return type since it represents
>> uncertainty in the latter. That is, the range of possible return
>> values would be [result - n*error,
>> result + n*error]. Do you have a case in mind where this isn't true?
> This is always true when you can define such an interval, which is
> not the case for an integral of a complex valued function ( no "<" on
> complex) .

I'm certainly not an expert in the numerical analysis involved in
convergence of complex
functions, but I imagine that this is essentially a subset of the
more general case of
vector-valued functions. For the latter case, the first-order
assumption is that error variances
are uncorrelated, leading to a diagonal covariance matrix between
components. In this
way, if a complex error was returned, it would indicate a gaussian
distributed set of errors
in the real and complex components forming an ellipse oriented with
the real and imaginary
axes. Naturally, covariances are important in many cases, but also
are more heavyweight.
I suppose that a N-dimensional result class could return an N-
dimensional value and an
NxN covariance matrix that reduced to diagonal in the case where
covariances are negligible...


Matthias Schabel, Ph.D.
Assistant Professor, Department of Radiology
Utah Center for Advanced Imaging Research
729 Arapeen Drive
Salt Lake City, UT 84108
801-587-9413 (work)
801-585-3592 (fax)
801-706-5760 (cell)
801-484-0811 (home)
matthias at stanfordalumni dot org

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