title: using curve fitting to determine complexity class of o-notation
body: <p>I am developing a java program that uses curve fitting techniques to determine the time complexities for o-notation. I am provided with input size and time, and i'm to determine which time complexity class it falls into by performing a regression on the data to find a curve fit . So far, i have been able to derive curves for x,x^2,x^3, e^x.... I am now trying to do the same for logx,xlogx,x^2logx by using a logarithmic regression that has the form of y=a+blogx. I have treated this as similar to a linear regression of a+bx, but swapping x for logx,xlogx,x^2logx and then performing gauss jordan elimination on it as i would for a linear curve. Is this a good approach, or should i be looking for an equation in the form of ax^2logx+bxlogx+c instead? I could use any clarifications or suggestions. Thanks </p>