saebnocov
0.1.0Small Area Estimation using Empirical Bayes without Auxiliary Variable
Overview
Estimates the parameter of small area in binary data without auxiliary variable using Empirical Bayes technique, mainly from Rao and Molina (2015,ISBN:9781118735787) with book entitled "Small Area Estimation Second Edition". This package provides another option of direct estimation using weight. This package also features alpha and beta parameter estimation on calculating process of small area. Those methods are Newton-Raphson and Moment which based on Wilcox (1979) doi:10.1177/001316447903900302 and Kleinman (1973) doi:10.1080/01621459.1973.10481332.
Install
Health
- OK2026-08-0413 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 7%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2022-09-05
- Total releases
- 1 / 4 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 13 KB / 1 file
- Download size
- 27 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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