| Package Name | Access | Summary | Updated |
|---|---|---|---|
| r-rdsg | public | A set of handy functions for Notre Dame Data Science Group | 2025-03-25 |
| mrbayes | public | Bayesian Inference of Phylogeny | 2025-03-25 |
| qqman | public | Draws Manhattan plot and QQ plot using plink assoc output. | 2025-03-25 |
| r-tda | public | Tools for the statistical analysis of persistent homology and for density clustering. For that, this package provides an R interface for the efficient algorithms of the C++ libraries 'GUDHI' <http://gudhi.gforge.inria.fr/>, 'Dionysus' <http://www.mrzv.org/software/dionysus/>, and 'PHAT' <https://bitbucket.org/phat-code/phat/>. This package also implements the methods in Fasy et al. (2014) <doi:10.1214/14-AOS1252> and Chazal et al. (2014) <doi:10.1145/2582112.2582128> for analyzing the statistical significance of persistent homology features. | 2025-03-25 |
| nbresuse | public | Simple Jupyter extension to show how much resources (RAM) your notebook is using | 2025-03-25 |
| r-pma | public | Performs Penalized Multivariate Analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis, described in the following papers: (1) Witten, Tibshirani and Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3):515-534. (2) Witten and Tibshirani (2009) Extensions of sparse canonical correlation analysis, with applications to genomic data. Statistical Applications in Genetics and Molecular Biology 8(1): Article 28. | 2025-03-25 |
| r-rafalib | public | A series of shortcuts for routine tasks originally developed by Rafael A. Irizarry to facilitate data exploration. | 2025-03-25 |
| r-cloudml | public | Interface to the Google Cloud Machine Learning Platform <https://cloud.google.com/ml-engine>, which provides cloud tools for training machine learning models. | 2025-03-25 |
| hg-git | public | Push and pull from git repositories using mercurial. | 2025-03-25 |
| r-hawkes | public | The package allows to simulate Hawkes process both in univariate and multivariate settings. It gives functions to compute different moments of the number of jumps of the process on a given interval, such as mean, variance or autocorrelation of process jumps on time intervals separated by a lag. | 2025-03-25 |
| jupyterlab-slurm | public | No Summary | 2025-03-25 |
| jupyterlab-latex | public | No Summary | 2025-03-25 |
| jupyterlab_katex-extension | public | No Summary | 2025-03-25 |
| jupyterlab-flake8 | public | No Summary | 2025-03-25 |
| jupyterlab-git | public | No Summary | 2025-03-25 |
| jupyterlab_geojson-extension | public | No Summary | 2025-03-25 |
| jupyterlab-github | public | No Summary | 2025-03-25 |
| jupyterlab_fasta-extension | public | No Summary | 2025-03-25 |
| jupyterlab-toc | public | No Summary | 2025-03-25 |
| jupyterlab-vim | public | No Summary | 2025-03-25 |
| jupyterlab-variableinspector | public | No Summary | 2025-03-25 |
| jupyterlab-hub | public | No Summary | 2025-03-25 |
| jupyterlab_html | public | No Summary | 2025-03-25 |
| jupyterlab-google-drive | public | No Summary | 2025-03-25 |
| jupyterlab_bokeh | public | No Summary | 2025-03-25 |
