Joint Modeling of Traditional and Environmental DNA Survey Data in a Bayesian Framework R package eDNAjoint version 0.3.3 Models integrate environmental DNA (eDNA) detection data and traditional survey data to jointly estimate species catch rate (see package vignette: <https://ednajoint.netlify.app/>). 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 gear scaling coefficients for traditional gear types. Models are implemented with a Bayesian framework (Markov chain Monte Carlo) using the 'Stan' probabilistic programming language. Software Depends: R (>= 4.1) Imports: bayestestR, dplyr, ggplot2, lifecycle, loo, methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rlist, rstan (>= 2.26.23), rstantools (>= 2.3.1.1), tidyr, scales LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.26.23), StanHeaders (>= 2.26.22) Suggests: bayesplot, knitr, rmarkdown, testthat (>= 3.0.0) Abigail G. Keller <agkeller@berkeley.edu> Comprehensive R Archive Network (CRAN) Abigail G. Keller [aut, cre], Ryan P. Kelly [ctb], Chitra M. Saraswati [rev], Saras M. Windecker [rev] GPL-3 2025-06-21 application/tgz https://CRAN.R-project.org/package=eDNAjoint doi:10.32614/CRAN.package.eDNAjoint