How to fit the 2D scatter data with a line with C++

Question

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 r

Answer 1

Fitting a Line can be acomplished in different ways. Least Square means minimizing the sum of the squared distance. But you could take another cost function as example the (not squared) distance. But normaly you use the squred distance (Least Square). There is also a possibility to define the distance in different ways. Normaly you just use the "y"-axis for the distance. But you could also use the total/orthogonal distance. There the distance is calculated in x- and y-direction. This can be a better fit if you have also errors in x direction (let it be the time of measurment) and you didn't start the measurment on the exact time you saved in the data. For Least Square and Total Least Square Line fit exist algorithms in closed form. So if you fitted with one of those you will get the line with the minimal sum of the squared distance to the datapoints. You can't fit a better line in the sence of your defenition. You could just change the definition as examples taking another cost function or defining distance in another way.

There is a lot of stuff about fitting models into data you could think of, but normaly they all use the "Least Square Line Fit" and you should be fine most times. But if you have a special case it can be necessary to think about what your doing. Taking Least Square done in maybe a few minutes. Thinking about what Method fits you best to the problem envolves understanding the math, which can take indefinit time :-).