saeczi

Provides functionality to fit a zero-inflated estimator for small area estimation. This estimator is a combines a linear mixed effects regression model and a logistic mixed effects regression model via a two-stage modeling approach. The estimator's mean squared error is estimated via a parametric bootstrap method. Chandra and others (2012, doi:10.1080/03610918.2011.598991) introduce and describe this estimator and mean squared error estimator. White and others (2024+, doi:10.48550/arXiv.2402.03263) describe the applicability of this estimator to estimation of forest attributes and further assess the estimator's properties.

Last 30 days

This package has been downloaded 374 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

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 5,486 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Feb 20, 2025 with 63 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.