Hi,
I couldn't find a in depth enough explanation in the documentation and I don't know c++ to be able to get this information from the source code, but I just wondered if anyone can expalin exactly how the weights in the "weights" argument in mxData is actually used mathematically? I know obviously a bigger weight will give more weight to that row of data etc, but I wanted a more detailed explanation than this if that's possible?
Thanks!
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A weight of 1.0 counts as a single observation. A weight of 2.0 is like you entered the same data twice as independent rows. A weight of 1.5 is halfway between these two cases. Make sense?
Thanks!
Ok so it's just like normal weighting. I wasn't sure if it did something more complicated under the hood, but that's great. Thank you for clarifying!
Well, it is a bit more complicated because fractional weights only work correctly for the maximum likelihood fit function. It doesn't work quite right with weighted least squares. On the other hand, row frequency (an integer) works in more cases.