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From: ice@trwrba.UUCP (Douglas L. Ice)
Newsgroups: net.math,net.micro,net.micro.pc
Subject: Re: simplex algorithsm for curve fitting---any disadvantage ??
Message-ID: <1836@trwrba.UUCP>
Date: Tue, 18-Feb-86 13:31:27 EST
Article-I.D.: trwrba.1836
Posted: Tue Feb 18 13:31:27 1986
Date-Received: Mon, 24-Feb-86 05:32:53 EST
References: <1217@princeton.UUCP> <236@vu-vlsi.UUCP>
Reply-To: ice@trwrba.UUCP (Douglas L. Ice)
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In article <236@vu-vlsi.UUCP> perry@vu-vlsi.UUCP (Rick Perry) writes:
>> I recently ported the curve fitting program, listed on BYTE 1984 May p.340,
>> The authors claimed that the program could fit *any* equation with *any*
>> number of parameters and variables to experimental data.
>
>[...]
>   The only disadvantage that I would note is that it has more or less linear
>convergence, so it may take more cpu time to get the answers with this method.
>But I like it for its stability and easy understandability - that is, you
>don't need 10 Ph.D.'s in math to comprehend how it works, and it's fairly
>easy to program in a straightforward, bug-free (if there is such a thing!)
>way.
>
>...Rick		...{pyrnj,psuvax1}!vu-vlsi!perry

In general, the simplex algorithm is classified as NP-complete -- in
other words, given an arbitrary set of variables and constraints, it
is currently unknown if the algorithm terminates in an amount of time
which is a polynomial function of the input length.  Many problems
whose only known solutions take time exponential in the input length
can be modeled using the simplex method (for example, the Travelling
Salesman problem).

Of course, there are many problems amenable to quick solution via the
simplex method, and, as Rick points out, it is dependable and simple(x).

---Doug