Can we apply non-linear smoothing to a linear looking like data ?

Click For Summary

Discussion Overview

The discussion revolves around the application of non-linear smoothing techniques to data that appears almost linear, particularly in the context of addressing discontinuities and enhancing linear correlations. Participants explore the implications of such smoothing methods in statistical analysis.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the validity of applying non-linear smoothing to nearly linear data, specifically in relation to removing discontinuities and strengthening linear correlations.
  • Another participant suggests that the effectiveness of non-linear smoothing may vary depending on the specific data series and the desired outcomes, indicating that statistics can guide the choice of smoothing coefficients.
  • A third participant expresses confusion about the mathematical problem being posed and emphasizes that the goal of the analysis needs to be clearly defined.
  • One participant proposes a quadratic model as a potential approach, suggesting a specific mathematical formulation to minimize the difference between observed and modeled values.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the appropriateness of non-linear smoothing for the given data. There are multiple competing views regarding its effectiveness and the necessity of defining the analytical goal.

Contextual Notes

Participants note the lack of a clearly defined mathematical problem and the ambiguity surrounding the intended outcomes of applying non-linear smoothing.

paawansharmas
Messages
19
Reaction score
0
My doubt is that whether we can apply non-linear smoothing to a almost linear data ( without one or 2 discontinuity)

I have attached the pic in which the red data is the smoothed one. Blue is the original one.
I multiplied each point with an increasing like 1, 1.1, 1.2, 1.3, 1.4...so on

My question is : is this valid way to remove discontinuity or to make a linear correlation stronger ??

thanks


attachment.php?attachmentid=57466&stc=1&d=1365086771.jpg
 

Attachments

  • 2pf.JPG
    2pf.JPG
    12.4 KB · Views: 511
Physics news on Phys.org
It really sounds like a question in the science of statistics.

For some series it'll make the linear correlation stronger, for some weaker. It probably depends on the effect you want, or the features you want to find in your data.

Statistics can also help you choose the correct coefficients for whatever kind of dampening.

So I advise you to ask this again in (or move the thread to) the statistics forum.
 
Thanks Amir.
But i do not know how to move it to other forum.
and if I write same thread in another forum , I will get warnings for multiple posting.

please help.

Thanks
Paawan
 
paawansharmas said:
My doubt is that whether we can apply non-linear smoothing to a almost linear data ( without one or 2 discontinuity)

To move a thread, you can use the "report" feature (even though the directions for report sound like it is only to be used to report naughty things) and "report" that you would like your thread moved.

You have not defined a mathematical problem. It isn't clear what you are trying to accomplish.

To take a silly point of view, you can do anything you want with the data. You could erase each value and write in a different number that pleases you! However, your question suggests you think only certain procedures will accomplish your goal. But what is the goal?
 
The answer to your question is 'yes'. Your curve looks like having a quadratic component. Take your model as Y= a+ bx + cx^2. Minimize sum[(y-Y)^2] with respect to a,b,c, where y= observed values.
 

Similar threads

  • · Replies 23 ·
Replies
23
Views
4K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 3 ·
Replies
3
Views
2K
Replies
2
Views
3K
Replies
3
Views
5K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
Replies
2
Views
2K
  • · Replies 36 ·
2
Replies
36
Views
5K
  • · Replies 5 ·
Replies
5
Views
2K