saekernel: Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel

Propose an area-level, non-parametric regression estimator based on Nadaraya-Watson kernel on small area mean. Adopt a two-stage estimation approach proposed by Prasad and Rao (1990). Mean Squared Error (MSE) estimators are not readily available, so resampling method that called bootstrap is applied. This package are based on the model proposed in Two stage non-parametric approach for small area estimation by Pushpal Mukhopadhyay and Tapabrata Maiti(2004) <http://www.asasrms.org/Proceedings/y2004/files/Jsm2004-000737.pdf>.

Package details

AuthorWicak Surya Hasani[aut, cre], Azka Ubaidillah[aut]
MaintainerWicak Surya Hasani <221710052@stis.ac.id>
LicenseGPL-3
Version0.1.1
URL https://github.com/wicaksh/saekernel
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("saekernel")

Try the saekernel package in your browser

Any scripts or data that you put into this service are public.

saekernel documentation built on June 4, 2021, 9:07 a.m.