xLLiM

High Dimensional Locally-Linear Mapping

CRAN Package

Provides a tool for non linear mapping (non linear regression) using a mixture of regression model and an inverse regression strategy. The methods include the GLLiM model (see Deleforge et al (2015) doi:10.1007/s11222-014-9461-5) based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame et al (2016) doi:10.1016/j.jmva.2017.09.009) based on a mixture of Generalized Student distributions. The methods also include BLLiM (see Devijver et al (2017) doi:10.48550/arXiv.1701.07899) which is an extension of GLLiM with a sparse block diagonal structure for large covariance matrices (particularly interesting for transcriptomic data).


Documentation


Team


Insights

Last 30 days

This package has been downloaded 571 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.

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0 downloadsFeb 23, 2025
0 downloadsFeb 24, 2025
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10 downloadsMar 1, 2025
22 downloadsMar 2, 2025
17 downloadsMar 3, 2025
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35 downloadsMar 5, 2025
29 downloadsMar 6, 2025
15 downloadsMar 7, 2025
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14 downloadsMar 17, 2025
35 downloadsMar 18, 2025
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28 downloadsMar 21, 2025
10 downloadsMar 22, 2025
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31 downloadsMar 24, 2025
14 downloadsMar 25, 2025
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40 downloadsMar 28, 2025
13 downloadsMar 29, 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 8,436 times in the last 365 days. That's a lot of interest! Someone might even write a blog post about it. The day with the most downloads was Nov 05, 2024 with 92 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


Binaries


Dependencies

  • Imports11 packages
  • Suggests1 package
  • Reverse Suggests1 package