Package: saeMSPE
Type: Package
Title: Compute MSPE Estimates for the Fay Herriot Model and Nested
        Error Regression Model
Version: 1.2
Date: 2022-10-19
Authors@R: c(person("Peiwen", "Xiao", role = c("aut", "cre"),
                email = "2569613200@qq.com"),
               person("Xiaohui", "Liu", role = "aut"),
               person("Yuzi", "Liu", role = "aut"),
               person("Shaochu", "Liu", role = "aut"),
               person("Jiming", "Jiang", role = "ths"))
Maintainer: Peiwen Xiao <2569613200@qq.com>
Description: We describe a new R package entitled 'saeMSPE' for the well-known Fay Herriot model and nested error regression model in small area estimation. Based on this package, it is possible to easily compute various common mean squared predictive error (MSPE) estimators, as well as several existing variance component predictors as a byproduct, for these two models.
License: GPL (>= 2)
Depends: R (>= 3.5.0), Matrix, smallarea
Imports: Rcpp (>= 1.0.7)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.2.1
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2022-10-21 11:53:38 UTC; 25696
Author: Peiwen Xiao [aut, cre],
  Xiaohui Liu [aut],
  Yuzi Liu [aut],
  Shaochu Liu [aut],
  Jiming Jiang [ths]
Repository: CRAN
Date/Publication: 2022-10-21 12:12:37 UTC
Built: R 4.1.2; x86_64-apple-darwin17.0; 2022-10-22 10:40:40 UTC; unix
Archs: saeMSPE.so.dSYM
