CRAN

mase 0.1.2

Model-Assisted Survey Estimators

Released Oct 12, 2018 by Kelly McConville

This package cannot yet be used with Renjin it depends on other packages which are not available: Rdpack 0.10-1 and dplyr 0.7.7

Dependencies

Rdpack 0.10-1 dplyr 0.7.7 survey 3.34 magrittr 1.5 glmnet 2.0-16 foreach 1.4.4 Matrix 1.2-14 boot 1.3-20 rpms 0.3.0

A set of model-assisted survey estimators and corresponding variance estimators for single stage, unequal probability, without replacement sampling designs. All of the estimators can be written as a generalized regression estimator with the Horvitz-Thompson, ratio, post-stratified, and regression estimators summarized by Sarndal et al. (1992, ISBN:978-0-387-40620-6). Two of the estimators employ a statistical learning model as the assisting model: the elastic net regression estimator, which is an extension of the lasso regression estimator given by McConville et al. (2017) , and the regression tree estimator described in McConville and Toth (2017) . The variance estimators which approximate the joint inclusion probabilities can be found in Berger and Tille (2009) and the bootstrap variance estimator is presented in Mashreghi et al. (2016) .

Source

R

View GitHub Mirror

Release History