Package: ccva Type: Package Title: Climate Change Vulnerability Assessment with Constrained Latent Models Version: 0.1.1 Authors@R: person("Hassan", "Doosti", email = "hassan.doosti@mq.edu.au", role = c("aut", "cre", "cph"), comment = c(affiliation = "Macquarie University")) Description: A general framework for climate change vulnerability assessment (CCVA) of any species and any dataset. Variables are tagged as exposure, sensitivity or adaptive capacity; each component is computed from its own predictors by a chosen method; and the three components are combined into vulnerability. Methods range from the rule-based framework of Foden et al. (2013) and the conventional weighted index of Ofori et al. (2017) to shape-constrained additive models ('scam'), latent-variable structural equation models ('lavaan') in which vulnerability is inferred from observable proxies, and penalised regression ('glmnet') for high-dimensional predictors. Missing traits and outcomes are handled by full-information maximum likelihood. Ecological knowledge enters as explicit constraints on predictors, on each component's role and on the links between components. Diagnostics, validation against observed outcomes, bootstrap and weight-based uncertainty, calibrated risk predictions and plots for every step are included. License: GPL (>= 3) URL: https://github.com/DoostiH/ccva BugReports: https://github.com/DoostiH/ccva/issues Encoding: UTF-8 Depends: R (>= 4.1.0) Imports: ggplot2 (>= 3.4.0), lavaan (>= 0.6-12), stats, utils Suggests: scam, glmnet, knitr, rmarkdown, testthat (>= 3.0.0) VignetteBuilder: knitr Config/testthat/edition: 3 LazyData: true RoxygenNote: 7.3.1 Repository: https://doostih.r-universe.dev Date/Publication: 2026-10-23 04:18:15 UTC RemoteUrl: https://github.com/doostih/ccva RemoteRef: HEAD RemoteSha: 2101cc5cbcb7898d23a64db3f37cb763a3fb698a NeedsCompilation: no Packaged: 2026-10-23 13:50:07 UTC; root Author: Hassan Doosti [aut, cre, cph] (affiliation: Macquarie University) Maintainer: Hassan Doosti