In sci.math Phil Sherrod <[EMAIL PROTECTED]> wrote: : On 27-Apr-2004, Michael Hochster <[EMAIL PROTECTED]> wrote:
:> : This isn't a "simple linear regression" problem. It is a nonlinear :> : regression problem. There are a number of nonlinear regression programs :> : that can solve your problem for a and b. Here is such a program that I :> ran :> : through my NLREG program (http://www.nlreg.com) :> :> Yes, it is a simple linear regression problem: ordinary regression :> of y on e^-x. As the author of regression software, you should know :> better. : I agree, by transforming the input variables this function is easily : converted to a linear regression. But it can be handled more easily and : properly as a nonlienar regression where no transformations are required. : Remember that fitting a function to a transformed independent variable does : not always yield the same fitting parameter results as fitting the function : to the non-transformed input -- minimizing the sum of squared deviations for : X is not the same as log(X) or sin(X). The difference can be significant. There is a closed form for the a and b minimizing sum[y - a - b*e^(-x)]^2, provided by the usual linear regression formulas. Are you saying it is easier and/or more proper to do a numerical search for a and b? Mike . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
