Small Area Estimation for Continuous Zero Inflated Data R package saeczi version 0.2.0 Provides functionality to fit a zero-inflated estimator for small area estimation. This estimator is a combines a linear mixed effects regression model and a logistic mixed effects regression model via a two-stage modeling approach. The estimator's mean squared error is estimated via a parametric bootstrap method. Chandra and others (2012, <doi:10.1080/03610918.2011.598991>) introduce and describe this estimator and mean squared error estimator. White and others (2024+, <doi:10.48550/arXiv.2402.03263>) describe the applicability of this estimator to estimation of forest attributes and further assess the estimator's properties. Software Depends: R (>= 4.1.0) Imports: dplyr, lme4, purrr, progressr, furrr, future, rlang, Rcpp LinkingTo: Rcpp, RcppEigen Suggests: testthat (>= 3.0.0) Josh Yamamoto <joshuayamamoto5@gmail.com> Comprehensive R Archive Network (CRAN) Josh Yamamoto [aut, cre], Dinan Elsyad [aut], Grayson White [aut], Julian Schmitt [aut], Niels Korsgaard [aut], Kelly McConville [aut], Kate Hu [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=saeczi/LICENSE) 2024-06-06 application/tgz https://CRAN.R-project.org/package=saeczi doi:10.32614/CRAN.package.saeczi