How to plot the best fit when x-axis has only one value?

Hi everyone, my data and code is given below,

x1 = [9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,];
x2= [39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27];
y1=[2.49849031538000e-15,2.49502658466163e-15,2.49502495000000e-15,2.50264303379900e-15,2.49502658466163e-15,2.49502495000000e-15,2.49560122336855e-15,8.17662331186994e-16,6.29990432061625e-16,2.12956584547500e-15,1.91935478762000e-15,2.63195081946000e-15,3.12979948175000e-15,3.09444418405000e-15,3.09233615855000e-15,3.01050170545000e-15,3.06054718890000e-15,3.11567416400000e-15,3.13276918045000e-15,3.05145014445000e-15,2.99728379425000e-15,3.12172508790000e-15,2.56985506485000e-15,3.20864482505000e-15,2.97324731355000e-15,2.56209731145000e-15,1.64972623540000e-15,1.62535722858500e-15,1.54636514685000e-15,1.28859402225000e-15,1.46049846936000e-15,1.33810415355000e-15,1.14215819083000e-15,8.42920403255000e-16];
y2=[1.50485306240000e-18,1.50775125440000e-18,1.34939445270000e-18,1.46522490255000e-18,1.29700159840000e-18,1.07510058980000e-18,1.18186725355000e-18,6.96921304120000e-18,1.10896235555000e-18,1.88431177410000e-18,2.06954144735000e-18,3.69742782500000e-18,4.50267051220000e-18,5.18527090055000e-18,4.27703042175000e-18,4.08381752195000e-18,4.36270874670000e-18,3.90556129885000e-18,3.54560734945000e-18,2.57385028340000e-18,2.66198817935000e-18,3.65437028765000e-18,2.19580890635000e-18,2.08296552040000e-18,1.69517276020000e-18,1.56244075620000e-18,1.34416563130000e-18,1.63989745735000e-18,1.61394252125000e-18,1.55418026030000e-18,1.42952255035000e-18,1.29278442465000e-18,1.16687040735000e-18,1.29804106530000e-18];

 loglog(x1,y1,'*b') 
 hold on
loglog(x2,y2,'*r')

I need the first order best fit of this data and code,thanks.

[the cyclist]

This is what the data look like, for those interested.

[the cyclist]

It's not very clear what your goal is for this "fit". Do you want to predict or simulate values for x1 and x2 separately?

Are your trying to predict y values for values of x that are different from your x1 and x2? (That seems like a fool's errand.)

You need to tell us more about what you are planning to do with this fit.

[Safi ullah]

I need to find best fit line between the red and blue points

Answer 1

[Star Strider]

Try this:

x1 = [9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,9.384,];
x2= [39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27,39.27];
y1=[2.49849031538000e-15,2.49502658466163e-15,2.49502495000000e-15,2.50264303379900e-15,2.49502658466163e-15,2.49502495000000e-15,2.49560122336855e-15,8.17662331186994e-16,6.29990432061625e-16,2.12956584547500e-15,1.91935478762000e-15,2.63195081946000e-15,3.12979948175000e-15,3.09444418405000e-15,3.09233615855000e-15,3.01050170545000e-15,3.06054718890000e-15,3.11567416400000e-15,3.13276918045000e-15,3.05145014445000e-15,2.99728379425000e-15,3.12172508790000e-15,2.56985506485000e-15,3.20864482505000e-15,2.97324731355000e-15,2.56209731145000e-15,1.64972623540000e-15,1.62535722858500e-15,1.54636514685000e-15,1.28859402225000e-15,1.46049846936000e-15,1.33810415355000e-15,1.14215819083000e-15,8.42920403255000e-16];
y2=[1.50485306240000e-18,1.50775125440000e-18,1.34939445270000e-18,1.46522490255000e-18,1.29700159840000e-18,1.07510058980000e-18,1.18186725355000e-18,6.96921304120000e-18,1.10896235555000e-18,1.88431177410000e-18,2.06954144735000e-18,3.69742782500000e-18,4.50267051220000e-18,5.18527090055000e-18,4.27703042175000e-18,4.08381752195000e-18,4.36270874670000e-18,3.90556129885000e-18,3.54560734945000e-18,2.57385028340000e-18,2.66198817935000e-18,3.65437028765000e-18,2.19580890635000e-18,2.08296552040000e-18,1.69517276020000e-18,1.56244075620000e-18,1.34416563130000e-18,1.63989745735000e-18,1.61394252125000e-18,1.55418026030000e-18,1.42952255035000e-18,1.29278442465000e-18,1.16687040735000e-18,1.29804106530000e-18];

xv = reshape([x1; x2], [], 1);                      % Create X-Vector
YM = reshape([y1; y2], [], 1);                      % Create Y-Vector

DM = [xv(:) ones(size(xv(:)))];                     % Design Matrix

B = DM \ YM;                                        % Estimate Parameters
YFit = DM * B;                                      % Fit Regression For Plot
YFit = reshape(YFit, 2, [])';

figure(1)
loglog(x1,y1,'*b')
hold on
loglog(x2,y2,'*r')
plot([x1(1) x2(1)], YFit(1,:), '-pg')
hold off

[Safi ullah]

@ Star Strider thanks your code work well.

[Star Strider]

As always, my pleasure.