AI-GEOSTATS: Re: Linear regression

[Isobel Clark]

DigbyThe variance of the residuals (whether regression or kriging) is the sum of the squared residuals divided by the degrees of freedom. Since the "degrees of freedom" is a fixed number, minimising the variance is identical to minimising the sum of squared residuals.IsobelDigby Millikan [EMAIL PROTECTED] wrote:Is minimizing the sum of the square of the the residuals equal to the minimization  of the variance of the residuals? Can we get any intuitive meaning from the relationship  between the sum of the squares and the variance?

AI-GEOSTATS: Re: Linear regression

[Digby Millikan]

Is there any intuitive meaning that the
mean square of the differences is

equal to the classical formulae for
variance? The variance can be written

in two different forms;



1. the variogram form.

2. the classical statistics variance form.



What are the properties, reasons for
expressing in these two different forms,

and what are the comparisons between the
two expressions.