4 views (last 30 days)
Nicholas Deosaran
Nicholas Deosaran on 14 Sep 2020
Answered: KSSV on 14 Sep 2020
I need help understing what to do here,
I know i need to slobe for p1 and p2x but stuck, I have the code below but just stuck.
x = 0:0.1:20;
noise =?? % a number, to define
y= 4*x + noise*rand(1,length(x));
Vary the value for noise as 0, 50 and 100 to get three different results for 饾憹1and 饾憹2,
From a linear algebra standpoint, determine the coefficients, 饾憹1and 饾憹2, of the least-squares-regression of a line fit through the data defined above.
thank you

Answers (1)

KSSV on 14 Sep 2020
Read about polyfit. If you have the data x, y you can fit a line and get p1, p2 using polyfit.
p = polyfit(x,y,1) ;
p1 = p(1) ; p2 = p(2) ;

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by