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>.


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install.packages("saekernel")

0.1.1 by Wicak Surya Hasani, 17 days ago


https://github.com/wicaksh/saekernel


Report a bug at https://github.com/wicaksh/saekernel/issues


Browse source code at https://github.com/cran/saekernel


Authors: Wicak Surya Hasani[aut, cre] , Azka Ubaidillah[aut]


Documentation:   PDF Manual  


GPL-3 license


Imports stats

Suggests knitr, rmarkdown, covr


See at CRAN