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**Olafson****Member**- Registered: 2014-02-11
- Posts: 1

Hello,

I am trying to construct a general function/method based on two sets of minimum/maximum data point constraints, which can take on new values in different situations. The only known data for this general function is the starting point (y-axis intercept) and the x-range. The rate of change over time must equal zero, so the amount increased/decreased must be compensated within the x-range. Optimally will vary as little as possible, as long as it meets the constraints.

I would appreciate any advice or suggestions on how to approach this problem as I've had very little success so far. Thank you in advance.

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**bobbym****Administrator**- From: Bumpkinland
- Registered: 2009-04-12
- Posts: 87,237

Hi Olafson;

Welcome to the forum. What does the data look like? What kind of regression model do you want?

For me to do anything with your problem I am going to need more information.

**In mathematics, you don't understand things. You just get used to them.Of course that result can be rigorously obtained, but who cares?Combinatorics is Algebra and Algebra is Combinatorics.**

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