updated codecov secret

ropensci · Sep 28, 2024 · 7b3efc5 · 7b3efc5
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -3,3 +3,4 @@
 ^README\.Rmd$
 ^\.github$
 ^codecov\.yml$
+^codemeta\.json$
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -5,7 +5,9 @@ Maintainer: Abigail G. Keller <agkeller@berkeley.edu>
 Author: Abigail G. Keller
 Authors@R: 
     c(person("Abigail G.", "Keller", role = c("aut", "cre"), email="agkeller@berkeley.edu"),
-    person("Ryan P.", "Kelly", role = "ctb", email="rpkelly@uw.edu"))
+    person("Ryan P.", "Kelly", role = "ctb", email="rpkelly@uw.edu"),
+    person("Chitra M.", "Saraswati", role = "rev"),
+    person("Saras M.", "Windecker", role = "rev"))
 Description: Models integrate environmental DNA (eDNA) detection data and traditional survey data to jointly estimate species catch rate (see package vignette: https://bookdown.org/abigailkeller/eDNAjoint_vignette/). Models can be used with count data via traditional survey methods (i.e., trapping, electrofishing, visual) and replicated eDNA detection/nondetection data via polymerase chain reaction (i.e., PCR or qPCR) from multiple survey locations. Estimated parameters include probability of a false positive eDNA detection, a site-level covariates that scale the sensitivity of eDNA surveys relative to traditional surveys, and catchability coefficients for traditional gear types. Models are implemented with a Bayesian framework (Markov chain Monte Carlo) using the 'Stan' probabilistic programming language.
 License: GPL-3
 URL: https://github.com/ropensci/eDNAjoint

diff --git a/NEWS.md b/NEWS.md
@@ -4,6 +4,7 @@
 -   Improved programming (i.e., reduced cyclomatic complexity, spacing, etc.)
 -   Added functionality to accommodate semi-paired data (i.e., traditional samples not collected at all surveyed sites).
 -   Improved integration of package print statements with user guide.
+-   Updated default calculation of initial values for MCMC.
 
 # eDNAjoint 0.1
 

diff --git a/README.Rmd b/README.Rmd
@@ -23,7 +23,7 @@ knitr::opts_chunk$set(
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/ropensci/eDNAjoint/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ropensci/eDNAjoint/actions/workflows/R-CMD-check.yaml)
-[![codecov](https://codecov.io/gh/abigailkeller/eDNAjoint/graph/badge.svg?token=AEVR9NSQ9Z)](https://codecov.io/gh/abigailkeller/eDNAjoint)
+[![codecov](https://codecov.io/gh/ropensci/eDNAjoint/graph/badge.svg?token=AEVR9NSQ9Z)](https://codecov.io/gh/ropensci/eDNAjoint)
 [![Status at rOpenSci Software Peer
 Review](https://badges.ropensci.org/642_status.svg)](https://github.com/ropensci/software-review/issues/642)
 [![Lifecycle:

diff --git a/README.md b/README.md
@@ -8,7 +8,7 @@
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/ropensci/eDNAjoint/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ropensci/eDNAjoint/actions/workflows/R-CMD-check.yaml)
-[![codecov](https://codecov.io/gh/abigailkeller/eDNAjoint/graph/badge.svg?token=AEVR9NSQ9Z)](https://codecov.io/gh/ropensci/eDNAjoint)
+[![codecov](https://codecov.io/gh/ropensci/eDNAjoint/graph/badge.svg?token=AEVR9NSQ9Z)](https://codecov.io/gh/ropensci/eDNAjoint)
 [![Status at rOpenSci Software Peer
 Review](https://badges.ropensci.org/642_status.svg)](https://github.com/ropensci/software-review/issues/642)
 [![Lifecycle:

diff --git a/codemeta.json b/codemeta.json
@@ -2,7 +2,7 @@
   "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
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   "identifier": "eDNAjoint",
-  "description": "Models integrate environmental DNA (eDNA) detection data and traditional survey data to jointly estimate species catch rate. Models can be used with count data via traditional survey methods (i.e., trapping, electrofishing, visual) and replicated eDNA detection/nondetection data via polymerase chain reaction (i.e., PCR or qPCR) from multiple survey locations. Estimated parameters include probability of a false positive eDNA detection, a site-level covariates that scale the sensitivity of eDNA surveys relative to traditional surveys, and catchability coefficients for traditional gear types. Models are implemented with a Bayesian framework (Markov chain Monte Carlo) using the 'Stan' probabilistic programming language.",
+  "description": "Models integrate environmental DNA (eDNA) detection data and traditional survey data to jointly estimate species catch rate (see package vignette: https://bookdown.org/abigailkeller/eDNAjoint_vignette/). Models can be used with count data via traditional survey methods (i.e., trapping, electrofishing, visual) and replicated eDNA detection/nondetection data via polymerase chain reaction (i.e., PCR or qPCR) from multiple survey locations. Estimated parameters include probability of a false positive eDNA detection, a site-level covariates that scale the sensitivity of eDNA surveys relative to traditional surveys, and catchability coefficients for traditional gear types. Models are implemented with a Bayesian framework (Markov chain Monte Carlo) using the 'Stan' probabilistic programming language.",
   "name": "eDNAjoint: Joint Modeling of Traditional and Environmental DNA Survey Data",
   "codeRepository": "https://github.com/ropensci/eDNAjoint",
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@@ -13,7 +13,7 @@
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@@ -39,6 +39,18 @@
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@@ -121,6 +133,18 @@
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@@ -132,7 +156,7 @@
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