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>.
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). 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.
You can install the released version of saekernel from CRAN with:
install.packages("saekernel")
Wicak Surya Hasani, Azka Ubaidillah
Wicak Surya Hasani [email protected]
saekernel() Produces Small Area Estimation Non-Parametric Based
Nadaraya-Watson Kernelmse_saekernel() Produces Small Area Estimation Non-Parametric
based Nadaraya-Watson Kernel and Bootstrap Mean Squared Error