I used to work with MATLAB, and for the question I raised I can use p = polyfit(x,y,1) to estimate the best fit line for the scatter data in a plate. I was wondering which resources I can rely on to implement the line fitting algorithm with C++. I understand there are a lot of algorithms for this subject, and for me I expect the algorithm should be fast and meantime it can obtain the comparable accuracy of polyfit function in MATLAB.
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I would suggest coding it from scratch. It is a very simple implementation in C++. You can code up both the intercept and gradient for least-squares fit (the same method as
polyfit) from your data directly from the formulas herehttp://en.wikipedia.org/wiki/Simple_linear_regression#Fitting_the_regression_line
These are closed form formulas that you can easily evaluate yourself using loops. If you were using higher degree fits then I would suggest a matrix library or more sophisticated algorithms but for simple linear regression as you describe above this is all you need. Matrices and linear algebra routines would be overkill for such a problem (in my opinion).