Other packages > Find by keyword >

mase  

Model-Assisted Survey Estimators
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mase", "0.1.5.2")



Attach the package and use:
library("mase")
Maintained by
Kelly McConville
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-14
Latest Update: 2024-01-17
Description:
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) .
How to cite:
Kelly McConville (2018). mase: Model-Assisted Survey Estimators. R package version 0.1.5.2, https://cran.r-project.org/web/packages/mase. Accessed 27 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:28), 0.1.1 (2018-06-14 20:33), 0.1.2 (2018-10-13 01:00), 0.1.3 (2021-07-10 01:00), 0.1.4 (2023-08-30 18:50), 0.1.5.1 (2023-11-27 22:50), 0.1.5 (2023-11-16 18:30)
Other packages that cited mase R package
View mase citation profile
Other R packages that mase depends, imports, suggests or enhances
Complete documentation for mase
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

lmmpar  
Parallel Linear Mixed Model
Embarrassingly Parallel Linear Mixed Model calculations spread across local cores which repeat until ...
Download / Learn more Package Citations See dependency  
BetterReg  
Better Statistics for OLS and Binomial Logistic Regression
Provides squared semi partial correlations, tolerance, Mahalanobis, Likelihood Ratio Chi Square, and ...
Download / Learn more Package Citations See dependency  
robustX  
'eXtra' / 'eXperimental' Functionality for Robust Statistics
Robustness -- 'eXperimental', 'eXtraneous', or 'eXtraordinary' Functionality for Robust Statistics. ...
Download / Learn more Package Citations See dependency  
risksetROC  
Riskset ROC Curve Estimation from Censored Survival Data
Compute time-dependent Incident/dynamic accuracy measures (ROC curve, AUC, integrated AUC )from cen ...
Download / Learn more Package Citations See dependency  
ROI.plugin.qpoases  
'qpOASES' Plugin for the 'R' Optimization Infrastructure
Enhances the 'R' Optimization Infrastructure ('ROI') package with the quadratic solver 'qpOASES'. M ...
Download / Learn more Package Citations See dependency  
Bodi  
Boosting Diversity in Regression Ensembles
A gradient boosting-based algorithm by incorporating a diversity term to guide the gradient boosting ...
Download / Learn more Package Citations See dependency  

28,332

R Packages

239,283

Dependencies

75,113

Author Associations

28,333

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA