fit a curve with smallest distance in y AND x direction to data points
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    F S
 am 22 Nov. 2017
  
    
    
    
    
    Kommentiert: Image Analyst
      
      
 am 27 Nov. 2017
            I have two sets of measurements x and y that seem to be correlated when plotting them against each other (below a small subsample of my data). I would like to fit a curve (linear, exponential, polynomial ..) through my data, such that it minimizes the distance of my points to the line (in an absolute or mean square way), but not only minimizing the distance on the y axis, but the closest distance in the x,y plane (euclidean distance). Is there a function/way to do that? As I understand it, most curve fitting functions in MATLAB fit the according to the rmse in y-direction only.
x =[1.3049    1.4137    0.2165    0.6538    0.6135    1.0655]
y =[4.0280    4.0865   50.1873   11.8024    7.9184    5.5866]
2 Kommentare
  Roger Stafford
      
      
 am 23 Nov. 2017
				If you use a fifth order polynomial, here's about as close as you can get:
X = [1.3049 1.4137  0.2165  0.6538 0.6135 1.0655];
Y = [4.0280 4.0865 50.1873 11.8024 7.9184 5.5866];
Y2 = 469.165558828655 - 3459.00108010757*X + 9145.4534625995*X.^2 ...
    - 11008.7869446613*X.^3 + 6175.46754074994*X.^4 - 1313.19614251125*X.^5;
x = linspace(.2,1.5);
y = 469.165558828655 - 3459.00108010757*x + 9145.4534625995*x.^2 ...
    - 11008.7869446613*x.^3 + 6175.46754074994*x.^4 - 1313.19614251125*x.^5;
[Y;Y2]
plot(x,y,'y-',X,Y2,'yo',X,Y,'r*')
Akzeptierte Antwort
  Jeff Miller
      
 am 22 Nov. 2017
        
      Bearbeitet: Image Analyst
      
      
 am 27 Nov. 2017
  
      It sounds like you want "orthogonal linear regression".
2 Kommentare
  Image Analyst
      
      
 am 27 Nov. 2017
				You might find the FAQ interesting: http://matlab.wikia.com/wiki/FAQ#How_can_I_fit_an_ellipse_or_other_shape_to_a_set_of_XY_data.3F
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