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it might be worth thinking about fitting the following: Y_ij = sigma_i sigma_j (l_i f_j + e_ij) where e_ij is N(0,1) l_i \sim g_l f_j \sim g_f
part of the idea is that the scaling might improve the exchangeability assumption on l and f.
(it is also possible that this would help with convergence?)
possibly we could start by looking at the GTEx data and investigating the effect of scaling rows and columns before analysis.
The text was updated successfully, but these errors were encountered:
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it might be worth thinking about fitting the following:
Y_ij = sigma_i sigma_j (l_i f_j + e_ij)
where
e_ij is N(0,1)
l_i \sim g_l
f_j \sim g_f
part of the idea is that the scaling might improve the exchangeability assumption on l and f.
(it is also possible that this would help with convergence?)
possibly we could start by looking at the GTEx data and investigating the effect of
scaling rows and columns before analysis.
The text was updated successfully, but these errors were encountered: