Is there a known general table of statistical techniques that explain how they scale with sample size and dimension? For example, a friend of mine told me the other day that the computation time of simply quick-sorting one dimensional data of size n goes as n*log(n).
So, for example, if we regress y against X where X is a d-dimensional variable, does it go as O(n^2*d)? How does it scale if I want to find the solution via exact Gauss-Markov solution vs numerical least squares with Newton method? Or simply getting the solution vs using significance tests?
I guess I more want a good source of answers (like a paper that summarizes the scaling of various statistical techniques) than a good answer here. Like, say, a list that includes the scaling of multiple regression, logistic regression, PCA, cox proportional hazard regression, K-means clustering, etc.