DESCRIPTION

Package: saeczi
Type: Package
Title: Small Area Estimation for Continuous Zero Inflated Data
Version: 0.2.0.9000
Authors@R: c(person("Josh", "Yamamoto", role = c("aut", "cre"),
                    email = "joshuayamamoto5@gmail.com"),
             person("Dinan", "Elsyad", role = "aut"),
             person("Grayson", "White", role = "aut"),
             person("Julian", "Schmitt", role = "aut"),
             person("Niels", "Korsgaard", role = "aut"),
             person("Kelly", "McConville", role = "aut"),
             person("Kate", "Hu", role = "aut"))
Maintainer: Josh Yamamoto <joshuayamamoto5@gmail.com>
Description: 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. 
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: 
    dplyr,
    lme4,
    purrr,
    progressr, 
    furrr,
    future,
    rlang,
    Rcpp
RoxygenNote: 7.3.1
Suggests: 
    testthat (>= 3.0.0)
Config/testthat/edition: 3
Depends: 
    R (>= 4.1.0)
LinkingTo:
    Rcpp,
    RcppEigen
URL: https://harvard-ufds.github.io/saeczi/