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Oxide example model fit may be an inappropriate model #743
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If you use a contrast like julia> first(m2.b)
2×24 Matrix{Float64}:
3.70686 -5.46891 2.67088 -0.979013 -1.71899 -2.75497 … -0.997343 -0.39882 -0.0995575 -0.178385 0.56977 -1.67469
-3.72693 5.49852 -2.68534 0.984313 1.7283 2.76988 -1.00222 -0.400768 -0.100044 -0.179257 0.572553 -1.68288 I'm not sure if that is a consequence of an unstable model or of only having 3 observations for each |
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One of the tests in
test/pls.jl
uses the:oxide
models defined intest/modelcache.jl
The second model is notoriously hard to fit. Different optimizers give very different parameter estimates but with similar values of the objective. I think this is because the model is ill-defined as
Source
is constant within eachLot
.To me this means that you can't expect to fit a random-effects term like
(1 + Source|Lot)
.Am I confusing myself?
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