Computes odds ratios and 95% confidence intervals from a generalized linear model object. It also computes model significance with the chi-squared statistic and p-value and it computes model fit using a contingency table to determine the percent of observations for which the model correctly predicts the value of the outcome. Calculates model sensitivity and specificity.

An implementation of the Blinder-Oaxaca decomposition for linear regression models.

Many treatment effect estimators can be written as weighted outcomes. These weights have established use cases like checking covariate balancing via packages like cobalt'. This package takes the original estimator objects and outputs these outcome weights. It builds on the general framework of Knaus (2024) <doi:10.48550/arXiv.2411.11559>. This version is compatible with the grf package and provides an internal implementation of Double Machine Learning.

This package provides new tools for analyzing discrete trait data integrating bio-ontologies and phylogenetics. It expands on the previous work of Tarasov et al. (2019) <doi:10.1093/isd/ixz009>. The PARAMO pipeline allows to reconstruct ancestral phenomes treating groups of morphological traits as a single complex character. The pipeline incorporates knowledge from ontologies during the amalgamation of individual character stochastic maps. Here we expand the current PARAMO functionality by adding new statistical methods for inferring evolutionary phenome dynamics using non-homogeneous Poisson process (NHPP). The new functionalities include: (1) reconstruction of evolutionary rate shifts of phenomes across lineages and time; (2) reconstruction of morphospace dynamics through time; and (3) estimation of rates of phenome evolution at different levels of anatomical hierarchy (e.g., entire body or specific regions only). The package also includes user-friendly tools for visualizing evolutionary rates of different anatomical regions using vector images of the organisms of interest.

Multiple tools are now available for inferring the personalised germ line set from an adaptive immune receptor repertoire. Output from these tools is converted to a single format and supplemented with rich data such as usage and characterisation of novel germ line alleles. This data can be particularly useful when considering the validity of novel inferences. Use of the analysis provided is described in <doi:10.3389/fimmu.2019.00435>.

Construct and evaluate directed tree structures that model the process of occurrence of genetic alterations during carcinogenesis as described in Szabo, A. and Boucher, K (2002) <doi:10.1016/S0025-5564(02)00086-X>.

This package provides a simple R interface to the OPUS Miner algorithm (implemented in C++) for finding the top-k productive, non-redundant itemsets from transaction data. The OPUS Miner algorithm uses the OPUS search algorithm to efficiently discover the key associations in transaction data, in the form of self-sufficient itemsets, using either leverage or lift. See <http://i.giwebb.com/index.php/research/association-discovery/> for more information in relation to the OPUS Miner algorithm.

I tend to repeat the same code chunks over and over again. At first, this was fine for me and I paid little attention to such redundancies. A little later, when I got tired of manually replacing Linux filepaths with the referring Windows versions, and vice versa, I started to stuff some very frequently used work-steps into functions and, even later, into a proper R package. And that's what this package is - a hodgepodge of various R functions meant to simplify (my) everyday-life coding work without, at the same time, being devoted to a particular scope of application.

This package provides functions for quickly creating R and Python scripts, as well as Rmarkdown or Quarto documents with automatically assigned name prefixes. Prefixes are either file counts (e.g. "001") or dates (e.g. "2022-09-26").

An interface to the search API of HAL <https://hal.science/>, the French open archive for scholarly documents from all academic fields. This package provides programmatic access to the API <https://api.archives-ouvertes.fr/docs> and allows to search for records and download documents.

This package provides a single function options.ifunset(...) is contained herewith, which allows the user to set a global option ONLY if it is not already set. By this token, for package maintainers this function can be used in preference to the standard options(...) function, making provision for THEIR end user to place options(...) directives within their .Rprofile file, which will not be overridden at the point when a package is loaded.

This package provides a novel method to implement cancer subtyping and subtype specific drug targets identification via non-negative matrix tri-factorization. To improve the interpretability, we introduce orthogonal constraint to the row coefficient matrix and column coefficient matrix. To meet the prior knowledge that each subtype should be strongly associated with few gene sets, we introduce sparsity constraint to the association sub-matrix. The average residue was introduced to evaluate the row and column cluster numbers. This is part of the work "Liver Cancer Analysis via Orthogonal Sparse Non-Negative Matrix Tri- Factorization" which will be submitted to BBRC.

This package provides a unified object-oriented framework for numerical optimizers in R. Supports minimization and maximization with any optimizer, optimization over more than one function argument, computation time measurement, and time limits for long optimization tasks.

Advanced forecasting algorithms for long-term energy demand at the national or regional level. The methodology is based on Grandón et al. (2024) <doi:10.1016/j.apenergy.2023.122249>; Zimmermann & Ziel (2024) <doi:10.1016/j.apenergy.2025.125444>. Real-time data, including power demand, weather conditions, and macroeconomic indicators, are provided through automated API integration with various institutions. The modular approach maintains transparency on the various model selection processes and encompasses the ability to be adapted to individual needs. oRaklE tries to help facilitating robust decision-making in energy management and planning.

This package provides a set of tools that enables using OxCal from within R. OxCal (<https://c14.arch.ox.ac.uk/oxcal.html>) is a standard archaeological tool intended to provide 14C calibration and analysis of archaeological and environmental chronological information. OxcAAR allows simple calibration with Oxcal and plotting of the results as well as the execution of sophisticated ('OxCal') code and the import of the results of bulk analysis and complex Bayesian sequential calibration.

Empirical reservoir water quality modelling using Walker's BATHTUB Model 1 (second-order available-phosphorus sedimentation) from Walker (1985) <https://hdl.handle.net/11681/13884> and Walker (1996) <https://hdl.handle.net/11681/4353> as the default retention model. The Vollenweider (1976) hydraulic- residence form and the equivalent formulation of Larsen and Mercier (1976) are available as alternatives. Predicts in-lake total phosphorus, total nitrogen, chlorophyll-a, and Secchi depth from tributary nutrient and hydraulic loading inputs, and computes Carlson (1977) <doi:10.4319/lo.1977.22.2.0361> Trophic State Indices. Optional Oklahoma-specific chlorophyll and Secchi regression coefficients are provided, calibrated from publicly available state lake monitoring data. Supports single-segment and multi-segment reservoir configurations and load-reduction scenario analysis. Designed to complement watershed loading models such as the Soil and Water Assessment Tool ('SWAT'; <https://swat.tamu.edu>) and the U.S. EPA Hydrologic and Water Quality System ('HAWQS'; <https://hawqs.tamu.edu>) in a two-model nutrient management workflow.

Search and extract data from the Organization for Economic Cooperation and Development (OECD).

Three-dimensional rendering for grid and ggplot2 graphics using cubes and cuboids drawn with an oblique projection. As a special case also supports primary view orthographic projections. Can be viewed as an extension to the isocubes package <https://github.com/coolbutuseless/isocubes>.

Enables the usage of the OpenDota API from <https://www.opendota.com/>, get game lists, and download JSON's of parsed replays from the OpenDota API. Also has functionality to execute own code to extract the specific parts of the JSON file.

This package provides functions for optimal policy learning in socioeconomic applications helping users to learn the most effective policies based on data in order to maximize empirical welfare. Specifically, OPL allows to find "treatment assignment rules" that maximize the overall welfare, defined as the sum of the policy effects estimated over all the policy beneficiaries. Documentation about OPL is provided by several international articles via Athey et al (2021, <doi:10.3982/ECTA15732>), Kitagawa et al (2018, <doi:10.3982/ECTA13288>), Cerulli (2022, <doi:10.1080/13504851.2022.2032577>), the paper by Cerulli (2021, <doi:10.1080/13504851.2020.1820939>) and the book by Gareth et al (2013, <doi:10.1007/978-1-4614-7138-7>).

Distributed reproducible computing framework, adopting ideas from git, docker and other software. By defining a lightweight interface around the inputs and outputs of an analysis, a lot of the repetitive work for reproducible research can be automated. We define a simple format for organising and describing work that facilitates collaborative reproducible research and acknowledges that all analyses are run multiple times over their lifespans.

Uses the outputs of a logistic regression model, from caret <https://CRAN.R-project.org/package=caret>, to build an odds plot. This allows for the rapid visualisation of odds plot ratios and works best with the outputs of CARET's GLM model class, by returning the final trained model.

An assortment of helper functions for managing data (e.g., rotating values in matrices by a user-defined angle, switching from row- to column-indexing), dates (e.g., intuiting year from messy date strings), handling missing values (e.g., removing elements/rows across multiple vectors or matrices if any have an NA), text (e.g., flushing reports to the console in real-time); and combining data frames with different schema (copying, filling, or concatenating columns or applying functions before combining).

This is a tool to find the optimal rerandomization threshold in non-sequential experiments. We offer three procedures based on assumptions made on the residuals distribution: (1) normality assumed (2) excess kurtosis assumed (3) entire distribution assumed. Illustrations are included. Also included is a routine to unbiasedly estimate Frobenius norms of variance-covariance matrices. Details of the method can be found in "Optimal Rerandomization via a Criterion that Provides Insurance Against Failed Experiments" Adam Kapelner, Abba M. Krieger, Michael Sklar and David Azriel (2020) <arXiv:1905.03337>.