plsmmLasso

Variable Selection and Inference for Partial Semiparametric Linear Mixed-Effects Model

CRAN Package

Implements a partial linear semiparametric mixed-effects model (PLSMM) featuring a random intercept and applies a lasso penalty to both the fixed effects and the coefficients associated with the nonlinear function. The model also accommodates interactions between the nonlinear function and a grouping variable, allowing for the capture of group-specific nonlinearities. Nonlinear functions are modeled using a set of bases functions. Estimation is conducted using a penalized Expectation-Maximization algorithm, and the package offers flexibility in choosing between various information criteria for model selection. Post-selection inference is carried out using a debiasing method, while inference on the nonlinear functions employs a bootstrap approach.


Documentation


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Insights

Last 30 days

This package has been downloaded 167 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

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0 downloadsFeb 9, 2025
0 downloadsFeb 10, 2025
0 downloadsFeb 11, 2025
9 downloadsFeb 12, 2025
7 downloadsFeb 13, 2025
5 downloadsFeb 14, 2025
6 downloadsFeb 15, 2025
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2 downloadsFeb 17, 2025
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9 downloadsMar 1, 2025
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4 downloadsMar 10, 2025
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3 downloadsMar 13, 2025
0 downloadsMar 14, 2025
0 downloadsMar 15, 2025
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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 2,095 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 Jun 07, 2024 with 38 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.

Data provided by CRAN


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Dependencies

  • Imports8 packages