Tree-structured modelling of categorical predictors (Tutz and Berger (2018), <doi:10.1007/s11634-017-0298-6>) or measurement units (Berger and Tutz (2018), <doi:10.1080/10618600.2017.1371030>).

Model Selection Based on Combined Penalties. This package implements a stepwise forward variable selection algorithm based on a penalized likelihood criterion that combines the L0 with L2 or L1 norms.

This package provides a wrapper allowing SQL queries to be run on a Snowflake instance directly from an R script, by using the snowflake-connector-python package in the background.

This package creates interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. treeheatr utilizes the customizable ggparty package for drawing decision trees.

Download and compile any version of the IANA Time Zone Database (also known as Olson database) and make it current in your R session. Beware: on Windows Cygwin is required!

This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.

Identifies maximal differential cell populations in flow cytometry data taking into account dependencies between cell populations; flowGraph calculates and plots SpecEnr abundance scores given cell population cell counts.

The goal of sansSouci is to perform post hoc inference: in a multiple testing context, sansSouci provides statistical guarantees on possibly user-defined and/or data-driven sets of hypotheses.

This package is a set of R functions for generating precise figures. This tool helps you to create clean markdown reports about what you just discovered with your analysis script.

This package preloads class unions for defining/loading core OOMPA tools. It also includes vectorized operations for row-by-row means, variances, and t-tests. Finally, it provides new colorschemes.

This package provides tidy tools for quantifying how well a model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

This package provides functions to make useful (and pretty) plots for scientific plotting. Additional plotting features are added for base plotting, with particular emphasis on making attractive log axis plots.

This package converts between R and Simple Feature sf objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through Rcpp.

Red Eclipse is an arena shooter, created from the Cube2 engine. Offering an innovative parkour system and distinct but all potent weapons, Red Eclipse provides fast paced and accessible gameplay.

Minima is a one-size-fits-all Jekyll theme for writers. It's Jekyll's default (and first) theme. It's what you get when you run jekyll new.

Process phylogenetic trees with tropical support vector machine and principal component analysis defined with tropical geometry. Details about tropical support vector machine are available in : Tang, X., Wang, H. & Yoshida, R. (2020) <arXiv:2003.00677>. Details about tropical principle component analysis are available in : Page, R., Yoshida, R. & Zhang L. (2020) <doi:10.1093/bioinformatics/btaa564> and Yoshida, R., Zhang, L. & Zhang, X. (2019) <doi:10.1007/s11538-018-0493-4>.

Implemented fast and memory-efficient Notch-filter, Welch-periodogram, discrete wavelet spectrogram for minutes of high-resolution signals, fast 3D convolution, image registration, 3D mesh manipulation; providing fundamental toolbox for intracranial Electroencephalography (iEEG) pipelines. Documentation and examples about RAVE project are provided at <https://rave.wiki>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see citation("ravetools") for details.

Detecting outliers using robust methods, i.e. the Median Absolute Deviation (MAD) for univariate outliers; Leys, Ley, Klein, Bernard, & Licata (2013) <doi:10.1016/j.jesp.2013.03.013> and the Mahalanobis-Minimum Covariance Determinant (MMCD) for multivariate outliers; Leys, C., Klein, O., Dominicy, Y. & Ley, C. (2018) <doi:10.1016/j.jesp.2017.09.011>. There is also the more known but less robust Mahalanobis distance method, only for comparison purposes.

Infer log-linear Poisson Graphical Model with an auxiliary data set. Hot-deck multiple imputation method is used to improve the reliability of the inference with an auxiliary dataset. Standard log-linear Poisson graphical model can also be used for the inference and the Stability Approach for Regularization Selection (StARS) is implemented to drive the selection of the regularization parameter. The method is fully described in <doi:10.1093/bioinformatics/btx819>.

An implementation of a method based on information theory devised for the identification of genes showing a significant variation of expression across multiple conditions. Given expression estimates from any number of RNA-Seq samples and conditions it identifies genes or transcripts with a significant variation of expression across all the conditions studied, together with the samples in which they are over- or under-expressed. Zambelli et al. (2018) <doi:10.1093/nar/gky055>.

This package provides fast algorithms for the Theil-Sen estimator, Siegel's repeated median slope estimator, and Passing-Bablok regression. The implementation is based on algorithms by Dillencourt et al. (1992) <doi:10.1142/S0218195992000020> and Matousek et al. (1998) <doi:10.1007/PL00009190>. The implementations are detailed in Raymaekers (2023) <doi:10.32614/RJ-2023-012> and Raymaekers J., Dufey F. (2022) <arXiv:2202.08060>. All algorithms run in quasilinear time.

Extends package arules with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration. Michael Hahsler (2017) <doi:10.32614/RJ-2017-047>.

This package provides a set of functions for interacting with the DigitalOcean API <https://www.digitalocean.com/>, including creating images, destroying them, rebooting, getting details on regions, and available images.

Estimate mixture cure models with subgroup survival probabilities as auxiliary information. A reference of the underlying methods is Jie Ding, Jialiang Li and Xiaoguang Wang (2024) <doi:10.1093/jrsssc/qlad106>.