Average of power curve functions

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SUMMARY

The discussion focuses on calculating the average of power curve functions represented by the equations: 4.638013x^0.076682586, 4.834884x^0.034875062, 4.0432342x^0.13476002, and 3.8535004x^0.12178477. The suggested method for finding the average function involves calculating the mean of the coefficients and the mean of the exponents separately. This approach aims to create a single curve that visually represents the collective behavior of the original functions, particularly for approximating mouse sensor motion reporting. The discussion emphasizes the need for clarity on the purpose of the average function, especially given the limitations of using a simple power curve.

PREREQUISITES
  • Understanding of power curve functions and their mathematical representation
  • Familiarity with polynomial equations and their properties
  • Basic knowledge of statistical averaging techniques
  • Experience with graphing programs for visual data representation
NEXT STEPS
  • Research methods for calculating averages of non-linear functions
  • Explore higher order polynomial approximations for better accuracy
  • Learn about noise reduction techniques in data sampling
  • Investigate graphing tools that support power curve fitting
USEFUL FOR

Data analysts, software developers working with sensor data, and mathematicians interested in curve fitting and approximation techniques will benefit from this discussion.

Labyrinth
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I have a program that generates a bunch of power curve functions and would like to know what the 'average' function between all of them would be.

Here is my data set so far:

4.638013x^0.076682586
4.834884x^0.034875062
4.0432342x^0.13476002
3.8535004x^0.12178477

How do I do this, and what is the average function for this particular set?

Thank you for your time.
 
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It depends on what you mean by 'average'.
 
I think the mean would be ideal.

I'm looking at it from a graph standpoint, where I want to find one curve that best represents them all.
 
I would lean toward taking the average of the four coefficients (the numbers in front of the power functions), and the average of the four exponents. That would certainly give you a function whose graph would be somewhere in the middle of the other four.
 
Is it really that simple? I guess I had delusions of complexity.

Anyways thanks for your help.
 
Labyrinth said:
Is it really that simple?

The un-simple task you have not done is to figure out precisely what you are trying to accomplish. What do you intend to use this "average" function for?
 
Stephen Tashi said:
The un-simple task you have not done is to figure out precisely what you are trying to accomplish. What do you intend to use this "average" function for?

I'm attempting to approximate the faulty motion reporting of a mouse sensor in terms of a power curve which it doesn't really follow but is available to mimic in settings available with many interfaces that support acceleration. The data I get is a bit noisy, so I take a sample, approximate its curve with a graphing program, take another sample, approximate that one, and so on. Over many iterations the 'average' function between them all should be a reasonable approximation.

There's a definite limit on the precision as long as only a simple power curve is available. It's more precisely described as a higher order polynomial. At a later date I may get into its exact description in these terms but for now a simple power curve takes priority.
 

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