saeczi
Small Area Estimation for Continuous Zero Inflated Data
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | saeczi_0.2.0.tar.gz |
398.2 KiB |
0.2.0 |
rolling linux/noble R-4.5 | saeczi_0.2.0.tar.gz |
400.7 KiB |
0.2.0 |
rolling source/ R- | saeczi_0.2.0.tar.gz |
306.7 KiB |
0.2.0 |
latest linux/jammy R-4.5 | saeczi_0.2.0.tar.gz |
398.2 KiB |
0.2.0 |
latest linux/noble R-4.5 | saeczi_0.2.0.tar.gz |
400.7 KiB |
0.2.0 |
latest source/ R- | saeczi_0.2.0.tar.gz |
306.7 KiB |
0.2.0 |
2026-04-26 source/ R- | saeczi_0.2.0.tar.gz |
306.7 KiB |
0.2.0 |
2026-04-23 source/ R- | saeczi_0.2.0.tar.gz |
306.7 KiB |
0.2.0 |
2026-04-09 windows/windows R-4.5 | saeczi_0.2.0.zip |
721.5 KiB |
0.2.0 |
2025-04-20 source/ R- | saeczi_0.2.0.tar.gz |
306.7 KiB |