Fix URL

README.Rmd

@@ -19,7 +19,7 @@ knitr::opts_chunk$set(
 <!--[![cran](https://www.r-pkg.org/badges/version/jagstargets)](https://cran.r-project.org/package=jagstargets)-->
 [![status](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
 [![check](https://github.com/ropensci/jagstargets/workflows/check/badge.svg)](https://github.com/ropensci/jagstargets/actions?query=workflow%3Acheck)
-[![codecov](https://codecov.io/gh/ropensci/jagstargets/branch/main/graph/badge.svg?token=3T5DlLwUVl)](https://codecov.io/gh/ropensci/jagstargets)
+[![codecov](https://codecov.io/gh/ropensci/jagstargets/branch/main/graph/badge.svg?token=3T5DlLwUVl)](https://app.codecov.io/gh/ropensci/gittargets)
 [![lint](https://github.com/ropensci/jagstargets/workflows/lint/badge.svg)](https://github.com/ropensci/jagstargets/actions?query=workflow%3Alint)
 
 Bayesian data analysis usually incurs long runtimes and cumbersome custom code, and the process of prototyping and deploying custom [JAGS](https://mcmc-jags.sourceforge.io) models can become a daunting software engineering challenge. To ease this burden, the `jagstargets` R package creates [JAGS](https://mcmc-jags.sourceforge.io) pipelines that are concise, efficient, scalable, and tailored to the needs of Bayesian statisticians. Leveraging [`targets`](https://docs.ropensci.org/targets/), `jagstargets` pipelines automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom user-side code is required, and there is no need to manually configure branching, so `jagstargets` is easier to use than [`targets`](https://docs.ropensci.org/targets/) and [`R2jags`](https://CRAN.R-project.org/package=R2jags) directly.

README.md

@@ -8,7 +8,7 @@ Targetopia](https://img.shields.io/badge/R_Targetopia-member-blue?style=flat&lab
 <!--[![cran](https://www.r-pkg.org/badges/version/jagstargets)](https://cran.r-project.org/package=jagstargets)-->
 [![status](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
 [![check](https://github.com/ropensci/jagstargets/workflows/check/badge.svg)](https://github.com/ropensci/jagstargets/actions?query=workflow%3Acheck)
-[![codecov](https://codecov.io/gh/ropensci/jagstargets/branch/main/graph/badge.svg?token=3T5DlLwUVl)](https://codecov.io/gh/ropensci/jagstargets)
+[![codecov](https://codecov.io/gh/ropensci/jagstargets/branch/main/graph/badge.svg?token=3T5DlLwUVl)](https://app.codecov.io/gh/ropensci/jagstargets)
 [![lint](https://github.com/ropensci/jagstargets/workflows/lint/badge.svg)](https://github.com/ropensci/jagstargets/actions?query=workflow%3Alint)
 
 Bayesian data analysis usually incurs long runtimes and cumbersome