Small Area Estimation using Empirical Bayes without Auxiliary Variable R package saebnocov version 0.1.0 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>. Software Depends: R (>= 3.5.0) Imports: descr, dplyr, rlang, stats Suggests: knitr, rmarkdown Siti Rafika Fiandasari <fikafianda@gmail.com> Comprehensive R Archive Network (CRAN) Siti Rafika Fiandasari [aut, cre], Margaretha Ari Anggorowati [aut], Bahrul Ilmi Nasution [aut] GPL (>= 3) 2022-09-05 application/tgz https://CRAN.R-project.org/package=saebnocov doi:10.32614/CRAN.package.saebnocov