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@@ -156,6 +156,9 @@ solver, the constrained HE-NNLS re-frames the parameter estimation as a non-nega
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knock-on effect that the model solving might be close to singular - Milo will generate a warning for each nhood where this is the case. We therefore recommend you set `warning=FALSE`
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if running in an Rstudio notebook, or wrap the function call in `suppressWarnings()`.
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+As a guideline, we recommend that you use `solver="Fisher"` in `testNhoods` with a GLMM - if the system is well conditioned then the performance is superior to the HE/HE-NNLS
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+approaches and faster.
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As we are estimating variances, we also want these to be unbiased, so we use restricted maximum likelihood (`REML=TRUE`). Note that NB-GLMMs are by construction slower than
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NB-GLMs as there are additional matrix inversion steps that don't scale very nicely. While we have made every effort to reduce the computational burden we are still limited by the bounds of matrix algebra!
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