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Wrapper functions for customizing HTML tables from the gt package to the ONSV style.
This package provides a general framework for the application of cross-validation schemes to particular functions. By allowing arbitrary lists of results, origami accommodates a range of cross-validation applications. This implementation was first described by Coyle and Hejazi (2018) <doi:10.21105/joss.00512>.
Implementation of a procedure for generating samples from a mixed distribution of ordinal and normal random variables with a pre-specified correlation matrix and marginal distributions. The details of the method are explained in Demirtas et al. (2015) <DOI:10.1080/10543406.2014.920868>.
This package implements a tree-based method specifically designed for personalized medicine applications. By using genomic and mutational data, ODT efficiently identifies optimal drug recommendations tailored to individual patient profiles. The ODT algorithm constructs decision trees that bifurcate at each node, selecting the most relevant markers (discrete or continuous) and corresponding treatments, thus ensuring that recommendations are both personalized and statistically robust. This iterative approach enhances therapeutic decision-making by refining treatment suggestions until a predefined group size is achieved. Moreover, the simplicity and interpretability of the resulting trees make the method accessible to healthcare professionals. Includes functions for training the decision tree, making predictions on new samples or patients, and visualizing the resulting tree. For detailed insights into the methodology, please refer to Gimeno et al. (2023) <doi:10.1093/bib/bbad200>.
This package provides details such as Morphine Equivalent Dose (MED), brand name and opioid content which are calculated of all oral opioids authorized for sale by Health Canada and the FDA based on their Drug Identification Number (DIN) or National Drug Code (NDC). MEDs are calculated based on recommendations by Canadian Institute for Health Information (CIHI) and Von Korff et al (2008) and information obtained from Health Canada's Drug Product Database's monthly data dump or FDA Daily database for Canadian and US databases respectively. Please note in no way should output from this package be a substitute for medical advise. All medications should only be consumed on prescription from a licensed healthcare provider.
This package performs outrigger local polynomial regression/ distributional adaptation, using a score-matching spline estimator of the conditional score function. Details of the method can be found in Young, Shah and Samworth (2026) <doi:10.48550/arXiv.2603.11282>.
Data processing, visualisation and analysis of Limit Order Book event data.
R Interface to ONNX - Open Neural Network Exchange <https://onnx.ai/>. ONNX provides an open source format for machine learning models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
This package provides general purpose tools for helping users to implement steepest gradient descent methods for function optimization; for details see Ruder (2016) <arXiv:1609.04747v2>. Currently, the Steepest 2-Groups Gradient Descent and the Adaptive Moment Estimation (Adam) are the methods implemented. Other methods will be implemented in the future.
Useful functions for one-sample (individual level data) Mendelian randomization and instrumental variable analyses. The package includes implementations of; the Sanderson and Windmeijer (2016) <doi:10.1016/j.jeconom.2015.06.004> conditional F-statistic, the multiplicative structural mean model Hernán and Robins (2006) <doi:10.1097/01.ede.0000222409.00878.37>, and two-stage predictor substitution and two-stage residual inclusion estimators explained by Terza et al. (2008) <doi:10.1016/j.jhealeco.2007.09.009>.
Facilitates the automatic detection of acoustic signals, providing functions to diagnose and optimize the performance of detection routines. Detections from other software can also be explored and optimized. This package has been peer-reviewed by rOpenSci. Araya-Salas et al. (2022) <doi:10.1101/2022.12.13.520253>.
Automated reporting in Word and PowerPoint can require customization for each organizational template. This package works around this by adding standard reporting functions and an abstraction layer to facilitate automated reporting workflows that can be replicated across different organizational templates.
Providing mean partition for ensemble clustering by optimal transport alignment(OTA), uncertainty measures for both partition-wise and cluster-wise assessment and multiple visualization functions to show uncertainty, for instance, membership heat map and plot of covering point set. A partition refers to an overall clustering result. Jia Li, Beomseok Seo, and Lin Lin (2019) <doi:10.1002/sam.11418>. Lixiang Zhang, Lin Lin, and Jia Li (2020) <doi:10.1093/bioinformatics/btaa165>.
Apache OpenNLP jars and basic English language models.
This package provides a complete pipeline for systematic bibliometric mapping of occupational health and safety (OHS) evidence. Starting from reference files exported from major bibliographic databases such as Web of Science, Scopus, PubMed, Dimensions, EBSCO, and others, orisma automates ingestion, deduplication, relevance filtering, occupational risk category extraction, bibliometric analysis, and report generation. The package is related to bibliometric science mapping and evidence synthesis workflows described by Aria and Cuccurullo (2017) <doi:10.1016/j.joi.2017.08.007>, Westgate (2019) <doi:10.1002/jrsm.1374>, and Lajeunesse (2016) <doi:10.1111/2041-210X.12472>, but adds a domain-specific occupational safety and health layer. The package implements three original bibliometric indicators: (1) the Worker-Risk Disconnection Index (WRDI), measuring the proportion of studies that characterise an occupational risk without including direct worker exposure data; (2) the Risk Category Saturation Index (RCS), measuring the relative over- or under-representation of each risk category relative to a uniform baseline; and (3) the Material-Gap Profile (MGP), measuring the ratio between a material's known hazard potential and its coverage in the occupational health literature. Two additional preventive intelligence indicators are provided: (4) the Abstract Sufficiency Score (ASS, 0-5), a cumulative hierarchical index of the preventively useful information contained in an abstract; and (5) the Bridge Article Score (0-5), identifying studies that simultaneously address technology, hazardous agent, worker population, exposure measurement, and preventive recommendations. Risk categories are extracted using a built-in occupational risk dictionary of 58 categories anchored in ISO 45001:2018, INSST, NIOSH, and EU-OSHA frameworks, organised in six blocks: Safety, Industrial Hygiene, Ergonomics, Psychosociology, Biological Hazards, and Emerging Technologies. The dictionary is user-extensible. Outputs include bilingual HTML reports, occupational risk sheets, priority reading rankings, guided extraction matrices for systematic review, and reproducibility certificates with MD5 hashes.
This package provides functionalities and data structures to retrieve, analyze and visualize aviation data. It includes a client interface to the OpenSky API <https://opensky-network.org>. It allows retrieval of flight information, as well as aircraft state vectors.
Designed to enhance data validation and management processes by employing a set of functions that read a set of rules from a CSV or Excel file and apply them to a dataset. Funded by the National Renewable Energy Laboratory and Possibility Lab, maintained by the Moore Institute for Plastic Pollution Research.
This package provides a method that analyzes quality control metrics from multi-sample genomic sequencing studies and nominates poor quality samples for exclusion. Per sample quality control data are transformed into z-scores and aggregated. The distribution of aggregated z-scores are modelled using parametric distributions. The parameters of the optimal model, selected either by goodness-of-fit statistics or user-designation, are used for outlier nomination. Two implementations of the Cosine Similarity Outlier Detection algorithm are provided with flexible parameters for dataset customization.
This package provides a function for fitting various penalized Bayesian cumulative link ordinal response models when the number of parameters exceeds the sample size. These models have been described in Zhang and Archer (2021) <doi:10.1186/s12859-021-04432-w>.
This package provides a tool for interactive exploration of the results from omics experiments to facilitate novel discoveries from high-throughput biology. The software includes R functions for the bioinformatician to deposit study metadata and the outputs from statistical analyses (e.g. differential expression, enrichment). These results are then exported to an interactive JavaScript dashboard that can be interrogated on the user's local machine or deployed online to be explored by collaborators. The dashboard includes sortable tables, interactive plots including network visualization, and fine-grained filtering based on statistical significance.
Allows production of Microsoft corporate documents from R Markdown by reusing formatting defined in Microsoft Word documents. You can reuse table styles, list styles but also add column sections, landscape oriented pages. Table and image captions as well as cross-references are transformed into Microsoft Word fields, allowing documents edition and merging without issue with references; the syntax conforms to the bookdown cross-reference definition. Objects generated by the officer package are also supported in the knitr chunks. Microsoft PowerPoint presentations also benefit from this as well as the ability to produce editable vector graphics in PowerPoint and also to define placeholder where content is to be added.
This package provides tools to analyze and infer orthology and paralogy relationships between glutamine synthetase proteins in seed plants.
This package provides a database containing the names of the babies born in Ontario between 1917 and 2018. Counts of fewer than 5 names were suppressed for privacy.
This package provides a suite of functions for the design of case-control and two-phase studies, and the analysis of data that arise from them. Functions in this packages provides Monte Carlo based evaluation of operating characteristics such as powers for estimators of the components of a logistic regression model. For additional detail see: Haneuse S, Saegusa T and Lumley T (2011)<doi:10.18637/jss.v043.i11>.