mase

Model-Assisted Survey Estimators

CRAN Package

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) doi:10.1093/jssam/smw041, and the regression tree estimator described in McConville and Toth (2017) doi:10.48550/arXiv.1712.05708. The variance estimators which approximate the joint inclusion probabilities can be found in Berger and Tille (2009) doi:10.1016/S0169-7161(08)00002-3 and the bootstrap variance estimator is presented in Mashreghi et al. (2016) doi:10.1214/16-SS113.


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Last 30 days

This package has been downloaded 338 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.

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The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,999 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Dec 03, 2024 with 52 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

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Dependencies

  • Imports9 packages
  • Suggests4 packages
  • Linking To2 packages
  • Reverse Imports1 package