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pbs-assess · Feb 28, 2024 · 1ca4e6c · 1ca4e6c
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diff --git a/README.Rmd b/README.Rmd
@@ -77,7 +77,7 @@ citation("sdmTMB")
 ```
 
 Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett., J.T. Thorson.
-2022. sdmTMB: an R package for fast, flexible, and
+2024. sdmTMB: an R package for fast, flexible, and
 user-friendly generalized linear mixed effects models with
 spatial and spatiotemporal random fields. bioRxiv
 2022.03.24.485545; doi: <https://doi.org/10.1101/2022.03.24.485545>

diff --git a/README.md b/README.md
@@ -14,7 +14,7 @@
 
 sdmTMB is an R package that fits spatial and spatiotemporal GLMMs (Generalized Linear Mixed Effects Models) using Template Model Builder ([TMB](https://github.com/kaskr/adcomp)), [R-INLA](https://www.r-inla.org/), and Gaussian Markov random fields. One common application is for species distribution models (SDMs). See the [documentation site](https://pbs-assess.github.io/sdmTMB/) and a preprint:
 
-Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett, J.T. Thorson. 2022. sdmTMB: an R package for fast, flexible, and user-friendly generalized linear mixed effects models with spatial and spatiotemporal random fields. bioRxiv 2022.03.24.485545; doi: https://doi.org/10.1101/2022.03.24.485545
+Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett, J.T. Thorson. 2024. sdmTMB: an R package for fast, flexible, and user-friendly generalized linear mixed effects models with spatial and spatiotemporal random fields. bioRxiv 2022.03.24.485545; doi: https://doi.org/10.1101/2022.03.24.485545
 
 ## Table of contents
 
@@ -135,10 +135,10 @@ To cite sdmTMB in publications use:
 citation("sdmTMB")
 ```
 
-Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett. 2022. sdmTMB:
-an R package for fast, flexible, and user-friendly generalized linear
-mixed effects models with spatial and spatiotemporal random fields.
-bioRxiv 2022.03.24.485545; doi:
+Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett., J.T. Thorson.
+2024. sdmTMB: an R package for fast, flexible, and user-friendly
+generalized linear mixed effects models with spatial and spatiotemporal
+random fields. bioRxiv 2022.03.24.485545; doi:
 <https://doi.org/10.1101/2022.03.24.485545>
 
 A list of (known) publications that use sdmTMB can be found

diff --git a/header.md b/header.md
@@ -13,6 +13,6 @@
 
 sdmTMB is an R package that fits spatial and spatiotemporal GLMMs (Generalized Linear Mixed Effects Models) using Template Model Builder ([TMB](https://github.com/kaskr/adcomp)), [R-INLA](https://www.r-inla.org/), and Gaussian Markov random fields. One common application is for species distribution models (SDMs). See the [documentation site](https://pbs-assess.github.io/sdmTMB/) and a preprint:
 
-Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett. 2022. sdmTMB: an R package for fast, flexible, and user-friendly generalized linear mixed effects models with spatial and spatiotemporal random fields. bioRxiv 2022.03.24.485545; doi: https://doi.org/10.1101/2022.03.24.485545
+Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett, J.T. Thorson. 2024. sdmTMB: an R package for fast, flexible, and user-friendly generalized linear mixed effects models with spatial and spatiotemporal random fields. bioRxiv 2022.03.24.485545; doi: https://doi.org/10.1101/2022.03.24.485545
 
 ## Table of contents
diff --git a/inst/CITATION b/inst/CITATION
@@ -7,9 +7,10 @@ bibentry(
     person(c("Sean", "C."), "Anderson"),
     person(c("Eric", "J."), "Ward"),
     person(c("Philina", "A."), "English"),
-    person(c("Lewis", "A.", "K."), "Barnett")
+    person(c("Lewis", "A.", "K."), "Barnett"),
+    person(c("James", "T."), "Thorson")
   ),
-  year = "2022",
+  year = "2024",
   journal = "bioRxiv",
   volume = "2022.03.24.485545",
   doi = "10.1101/2022.03.24.485545"