Peter Dalgaard p.dalgaard at biostat.ku.dk writes:
The point is that R (as well as almost all other mainstream statistical
software) assumes that a weight means that the variance of the
corresponding observation is the general variance divided by the weight
factor. The general variance is
David Winsemius dwinsemius at comcast.net writes:
It's really not that difficult to get the variance covariance matrix.
What is not so clear is why you think differential weighting of a set
that has a perfect fit should give meaningfully different results than
a fit that has no
David Winsemius dwinsemius at comcast.net writes:
Which means those x, y, and error figures did not come from an
experiment, but rather from theory???
The fact is I am trying to compare the results of:
(1) lm under R and
(2) the Java applet at
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