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- Newsgroups: sci.math.stat
- Path: sparky!uunet!zaphod.mps.ohio-state.edu!pacific.mps.ohio-state.edu!linac!att!cbnewsc!cbfsb!cbnewsf.cb.att.com!rizzo
- From: rizzo@cbnewsf.cb.att.com (anthony.r.rizzo)
- Subject: least squares fit to function
- Message-ID: <1992Oct13.151606.8435@cbfsb.cb.att.com>
- Sender: news@cbfsb.cb.att.com
- Organization: AT&T
- Date: Tue, 13 Oct 1992 15:16:06 GMT
- Lines: 22
-
- Some time ago, I asked for net-wisdom on the subject of constrained
- least squares. Many of you responded, letting me know that I was
- on track. First, let me thank all those who responded. I've since
- written my own little program to do constrained least square fits
- of n-degree polynomials. But now I have a slightly off-the-wall
- question for you. Read on. ;-)
-
- Given some explicitely defined function g(x), say, g(x) = sin(x),
- can the method of least square errors be applied such that
- we derive a second function f(x) = a0 + a1*x + a2*x^2 + ... + an*x^n
- where f(x) is the best least squares fit to g(x)?
-
- I know that this request sounds strange. But I have a legitimate
- application. The application software that I'm using, ANSYS,
- forces me to input certain quantities as polynomial functions
- of temperature. So I can't get around using a polynomial.
- Given this restriction, I at least want to use a best-fit polynomial.
-
- Has anyone ever heard of this being done before?
-
- Tony Rizzo
-
-