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saekernel  

Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel
View on CRAN: Click here


Download and install saekernel package within the R console
Install from CRAN:
install.packages("saekernel")

Install from Github:
library("remotes")
install_github("cran/saekernel")

Install by package version:
library("remotes")
install_version("saekernel", "0.1.1")



Attach the package and use:
library("saekernel")
Maintained by
Wicak Surya Hasani
[Scholar Profile | Author Map]
First Published: 2021-06-04
Latest Update: 2021-06-04
Description:
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) .
How to cite:
Wicak Surya Hasani (2021). saekernel: Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel. R package version 0.1.1, https://cran.r-project.org/web/packages/saekernel. Accessed 28 Feb. 2025.
Previous versions and publish date:
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Complete documentation for saekernel
Functions, R codes and Examples using the saekernel R package
Some associated functions: Data_saekernel . mse_saekernel . saekernel . 
Some associated R codes: Data_saekernel.R . mse_saekernel.R . saekernel.R .  Full saekernel package functions and examples
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