This package provides test statistics, p-value, and confidence intervals based on 9 hypothesis tests for dependence.

This package provides methods for computing joint tests, controlling the Familywise Error Rate (FWER) and getting lower bounds on the number of false hypotheses in a set. The methods implemented here are described in Mogensen and Markussen (2021) <doi:10.48550/arXiv.2108.04731>.

This package provides utility functions to help researchers implement best practices for their coding projects. Includes tools for reading and cleaning data files, initializing R projects with a standard folder structure, creating Quarto documents from a reproducible template, detecting the execution context across interactive, Quarto, and script-based workflows, and splitting data frames into group-level output files.

This package provides functions for preparing and analyzing animal tracking data, with the intention of identifying areas which are potentially important at the population level and therefore of conservation interest. Areas identified using this package may be checked against global or regionally-defined criteria, such as those set by the Key Biodiversity Area program. The method published herein is described in full in Beal et al. 2021 <doi:10.1111/2041-210X.13713>.

Fitting time-varying coefficient models for single and multi-equation regressions, using kernel smoothing techniques.

This package provides new layer functions to tmap for creating various types of cartograms. A cartogram is a type of thematic map in which geographic areas are resized or distorted based on a quantitative variable, such as population. The goal is to make the area sizes proportional to the selected variable while preserving geographic positions as much as possible.

Evaluate inline or chunks of R code in template files and replace with their output modifying the resulting template.

This package provides comprehensive tools for conducting research using the Thinking Grid framework, a psychological measurement approach for understanding the stream of thought. Includes functions for generating Qualtrics surveys with the thinking grid, processing survey responses, calculating quadrant depths, and creating various visualization types including heatmaps, animations, and statistical plots. See Irving, Z. C., Murray, S., Kuvar, V., Urena, M., and Mills, C. (2025) "Consciousness, Just in Time: Fluctuations in the Stream of Consciousness during Tasks and Rest" (manuscript under review, draft available from zci7c@virginia.edu).

This package provides a tool that allows users to estimate tree height in the long-term forest experiments in Sweden. It utilizes the multilevel nonlinear mixed-effect height models developed for the forest experiments and consists of four functions for the main species, other conifer species, and other broadleaves. Each function within the system returns a data frame that includes the input data and the estimated heights for any missing values. Ogana et al. (2023) <doi:10.1016/j.foreco.2023.120843>\n Arias-Rodil et al. (2015) <doi:10.1371/JOURNAL.PONE.0143521>.

Pacote para a analise de experimentos com um ou dois fatores com testemunhas adicionais conduzidos no delineamento inteiramente casualizado ou em blocos casualizados. "Package for the analysis of one or two-way experiments with additional controls conducted in a completely randomized design or in a randomized block design".

This package provides functions that compute predictions from Generalised Additive Models (GAMs) fitted with mgcv and return them as a tibble. These can be plotted with a generic plot()-method that uses ggplot2 or plotted as any other data frame. The main function is predict_gam().

Fitting tree-structured varying coefficient models (Berger et al. (2019), <doi:10.1007/s11222-018-9804-8>). Simultaneous detection of covariates with varying coefficients and effect modifiers that induce varying coefficients if they are present.

This package provides a common way of validating a biological assay for is through a procedure, where m levels of an analyte are measured with n replicates at each level, and if all m estimates of the coefficient of variation (CV) are less than some prespecified level, then the assay is declared validated for precision within the range of the m analyte levels. Two limitations of this procedure are: there is no clear statistical statement of precision upon passing, and it is unclear how to modify the procedure for assays with constant standard deviation. We provide tools to convert such a procedure into a set of m hypothesis tests. This reframing motivates the m:n:q procedure, which upon completion delivers a 100q% upper confidence limit on the CV. Additionally, for a post-validation assay output of y, the method gives an ``effective standard deviation interval of log(y) plus or minus r, which is a 68% confidence interval on log(mu), where mu is the expected value of the assay output for that sample. Further, the m:n:q procedure can be straightforwardly applied to constant standard deviation assays. We illustrate these tools by applying them to a growth inhibition assay. This is an implementation of the methods described in Fay, Sachs, and Miura (2018) <doi:10.1002/sim.7528>.

Torch code for computing multi-class Area Under The Minimum, <https://www.jmlr.org/papers/v24/21-0751.html>, Generalization. Useful for optimizing Area under the curve.

Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). The package makes use of a free service provided by <https://stellarapi.io>.

This package provides tools to download data series from Banco de España ('BdE') on tibble format. Banco de España is the national central bank and, within the framework of the Single Supervisory Mechanism ('SSM'), the supervisor of the Spanish banking system along with the European Central Bank. This package is in no way sponsored endorsed or administered by Banco de España'.

An implementation of turtle graphics <http://en.wikipedia.org/wiki/Turtle_graphics>. Turtle graphics comes from Papert's language Logo and has been used to teach concepts of computer programming.

Link R with Transformers from Hugging Face to transform text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see <https://www.r-text.org>.

This package provides two classes extending data.table class. Simple tableList class wraps data.table and any additional structures together. More complex tableMatrix class combines data.table and matrix'. See <http://github.com/InferenceTechnologies/tableMatrix> for more information and examples.

Collect marketing data from TikTok Ads using the Windsor.ai API <https://windsor.ai/api-fields/>.

Estimation of transition probabilities for the illness-death model and or the three-state progressive model.

Create publication quality plots and tables for Item Response Theory and Classical Test theory based item analysis, exploratory and confirmatory factor analysis.

Execution of various time series models and choosing the best one either by a specific error metric or by picking the best one by majority vote. The models are based on the "forecast" package, written by Prof. Rob Hyndman.

Interacts with a suite of web application programming interfaces (API) for taxonomic tasks, such as getting database specific taxonomic identifiers, verifying species names, getting taxonomic hierarchies, fetching downstream and upstream taxonomic names, getting taxonomic synonyms, converting scientific to common names and vice versa, and more. Some of the services supported include NCBI E-utilities (<https://www.ncbi.nlm.nih.gov/books/NBK25501/>), Encyclopedia of Life (<https://eol.org/docs/what-is-eol/data-services>), Global Biodiversity Information Facility (<https://techdocs.gbif.org/en/openapi/>), and many more. Links to the API documentation for other supported services are available in the documentation for their respective functions in this package.