Hierarchical generalized additive models in ecology: an introduction with mgcv

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RT @ucfagls: If you want to fit nonlinear relationships to data where those relationships can vary by groups (eg species) then we have a pa…
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1031 days ago
@ChelseaParlett so like i'm in speech sciences so this survey was a godsend https://t.co/kY5sULNTJv but i imagine an ecologist would like this https://t.co/a1KhSMuSp2
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@bolkerb @chris_e_overton @RPatonOx @ericJpedersen @ucfagls @noamross @millerdl https://t.co/uFP2qJieFB key to the model formulation! A real favourite read in our team
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As you can see, individual (ind) and subpopulation (town) are random effects. I modelled my system after the GI-style model in the Pedersen et al. 2019 paper https://t.co/aDA10WG2Xj
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Hello #StatsTwitter. I constructed an HGAMM model after Pedersen et al. (2019) [https://t.co/wrCxniDRms], but in brms() and wanted to ask you all for your thoughts on my model specification and results. Please bear with me while I write this thread and explain everything. (1/n)
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Hierarchical generalized additive models in ecology: an introduction with mgcv [PeerJ] https://t.co/V3Ds69thPZ
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RT @icymi_r: ✍️ "Hierarchical generalized additive models in ecology • an introduction with mgcv [PeerJ]"
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RT @ucfagls: If you want to fit nonlinear relationships to data where those relationships can vary by groups (eg species) then we have a pa…
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RT @ChristelDBruijn: Hierarchical generalized additive models in ecology: an introduction with mgcv by @ucfagls @noamross @ericJpedersen…
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Hierarchical generalized additive models in ecology: an introduction with mgcv by @ucfagls @noamross @ericJpedersen For code see https://t.co/kY1CrAwqns https://t.co/ViPcTdBw9A
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RT @ucfagls: If you want to fit nonlinear relationships to data where those relationships can vary by groups (eg species) then we have a pa…
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1186 days ago
RT @ucfagls: If you want to fit nonlinear relationships to data where those relationships can vary by groups (eg species) then we have a pa…
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@TenanATC So I'm essentially fitting a GS model (https://t.co/dXTy2YLfgc)... For the 1k sample (~35k obs) gamm4 took ~1.5 hours on my build, and bam with discrete=TRUE, fREML, and nthreads=12 took ~20 mins.
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1238 days ago
RT @anordonez1: For more on thes Random GAMs https://t.co/cyJJzFUvbC
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For more on thes Random GAMs https://t.co/cyJJzFUvbC
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RT @ucfagls: If you want to fit nonlinear relationships to data where those relationships can vary by groups (eg species) then we have a pa…
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1257 days ago
RT @ericward_: @se_hampton @DrCraigMc @sl_katz @mark_scheuerell @eeholm We also have that as a course UW course webpage here, https://t.co/…
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1258 days ago
@se_hampton @DrCraigMc @sl_katz @mark_scheuerell @eeholm We also have that as a course UW course webpage here, https://t.co/Lu9atFlRyo or book version https://t.co/fhbAjyNLUM I'd also put in a plug for hierarchical GAMs as another way to deal with a prob like this -- see @ericJpedersen @millerdl et al. here:https://t.co/D1JdE76Gqj
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1259 days ago
@DrCraigMc @robjhyndman Maybe @ericJpedersen et al's work in hierarchical GAMs, then? https://t.co/eaQ2dBcbdH Not sure of the best place to start, I think they have a few R-based tutorials...
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RT @ucfagls: If you want to fit nonlinear relationships to data where those relationships can vary by groups (eg species) then we have a pa…
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Hierarchical generalized additive models in ecology: an introduction with mgcv https://t.co/dXTy2YKHqE
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RT @juliakemppinen: We used HGAMs (@ericJpedersen et al. 2019, the link) to understand if the patterns were consistent between the three ar…
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RT @juliakemppinen: We used HGAMs (@ericJpedersen et al. 2019, the link) to understand if the patterns were consistent between the three ar…
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We used HGAMs (@ericJpedersen et al. 2019, the link) to understand if the patterns were consistent between the three areas - they were! And cryoturbation most strongly influenced both structural and leaf economic traits. https://t.co/4a4JfzWhhD https://t.co/HRJtI8N9GN
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1350 days ago
@camjpatrick @mattansb @ellapouton
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