Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the ...

There is vast literature on M-estimation of linear regression parameters. Most of the papers deal with special cases by choosing particular discrepancy functions to be minimized or particular ...

That is the the basic form of linear regression by hand. Note that there ARE other ways to do this - more complicated ways (assuming different types of distributions for the data).

Nonlinear regression is a form of regression analysis in which data is fit to a model and then expressed as a mathematical function. Simple linear regression relates two variables (X and Y) with a ...