This package currently implements the unit level EBLUP and
GREG estimators as well as the estimate of their variances to
further document the publication of Breidenbach and Astrup
(2011). It also contains a vignette that explains the use of
the implemented functions.

Unit-Level and Area-Level Small Area Estimation
Implementation of some unit and area level EBLUP estimators as well as the estimators of their MSE also under heteroscedasticity. The package further documents the publications Breidenbach and Astrup (2012) <DOI:10.1007/s10342-012-0596-7>, Breidenbach et al. (2016) <DOI:10.1016/j.rse.2015.07.026> and Breidenbach et al. (2018 in press). The vignette further explains the use of the implemented functions.

RE.Johnson perform the Johnson Transformation for achieve
normality.

RE.Johnson performs the Johnson Transformation to increase the normality.

Johnson curve distributions.  Implementation of AS100 and
AS99.

Joint Analysis and Imputation of Incomplete Data
Provides joint analysis and imputation of linear regression models,
generalized linear regression models or linear mixed models with incomplete
(covariate) data in the Bayesian framework.
The package performs some preprocessing of the data and creates a 'JAGS'
model, which will then automatically be passed to 'JAGS'
<http://mcmc-jags.sourceforge.net> with the help of
the package 'rjags'.
It also provides summary and plotting functions for the output.

person("Nicole S.", "Erler", email = "n.erler@erasmusmc.nl",
role = c("aut", "cre"))

c(person("Nicole S.", "Erler", email = "n.erler@erasmusmc.nl",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-9370-6832")))
knitr, rmarkdown, foreign, ggplot2, reshape2

Provides joint analysis and imputation of (generalized)
linear regression models, (generalized) linear mixed models and parametric
survival models with incomplete (covariate) data in the Bayesian framework.
The package performs some preprocessing of the data and creates a 'JAGS'
model, which will then automatically be passed to 'JAGS'
<http://mcmc-jags.sourceforge.net> with the help of
the package 'rjags'.
It also provides summary and plotting functions for the output.