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predicted values with INLA #50
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Here is the function. https://github.com/daijiang/phyr/blob/master/R/pglmm-utils.R#L904-L911 |
Thanks Daijiang for the reminder. Looks like I chose to ignore the |
Russell, |
Daijiang and Russell,
Your explanation of tip_rm matches mine, but I think the prediction of nearest_node includes all of the tip values. I don't think I wrote this code, but maybe I did. Performing the nearest_node prediction with all data is equivalent to what you would do for a random effect – predict the value of the random effect from all data. The problem with phylogenies is that the branch length between tips and nearest nodes can be very short.
I'm not exactly sure what INLA is doing, but the values I get are similar to nearest_node as described above when bayes = F.
Cheers, Tony
From: Daijiang Li <[email protected]>
Reply-To: daijiang/phyr <[email protected]>
Date: Thursday, June 18, 2020 at 6:51 PM
To: daijiang/phyr <[email protected]>
Cc: "Anthony R. Ives" <[email protected]>, Mention <[email protected]>
Subject: Re: [daijiang/phyr] predicted values with INLA (#50)
Russell, tip_rm means removing a record (sort of like remove a tip species from a phylogeny) and then using the remaining data to predict the value. nearest_node means after removing the record, make prediction for the most common ancestor instead of itself. @arives<https://github.com/arives> probably can correct me and explain better here.
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Russell,
While updating rr2, I found that the bayes=T version of pglmm returns the "nearest_node" predicted values even when the "tip_rm" option is used. Is there a structural reason for this? For R2_pred, the "tip_rm" option makes more sense.
Thanks, Tony
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