This package provides a collection of functions related to density estimation by using Chen's (2000) idea. Mean Squared Errors (MSE) are calculated for estimated curves. For this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull. For details see Chen (2000), Scaillet (2004) <doi:10.1080/10485250310001624819> and Khan and Akbar.

Check if a given package name is available to use. It checks the name's validity. Checks if it is used on GitHub', CRAN and Bioconductor'. Checks for unintended meanings by querying Wiktionary and Wikipedia.

Simple and transparent parsing of genotype/dosage data from an input Variant Call Format (VCF) file, matching of genotype coordinates to the component Single Nucleotide Polymorphisms (SNPs) of an existing polygenic score (PGS), and application of SNP weights to dosages for the calculation of a polygenic score for each individual in accordance with the additive weighted sum of dosages model. Methods are designed in reference to best practices described by Collister, Liu, and Clifton (2022) <doi:10.3389/fgene.2022.818574>.

Perform one-dimensional spline regression with automatic knot selection. This package uses a penalized approach to select the most relevant knots. B-splines of any degree can be fitted. More details in Goepp et al. (2018)', "Spline Regression with Automatic Knot Selection", <arXiv:1808.01770>.

This package provides a suite of functions for analyzing sequences of events. Users can generate and code sequences based on predefined rules, with a special focus on the identification of sequences coded as ABA (when one element appears, followed by a different one, and then followed by the first). Additionally, the package offers the ability to calculate the length of consecutive ABA'-coded sequences sharing common elements. The methods implemented in this package are based on the work by Ziembowicz, K., Rychwalska, A., & Nowak, A. (2022). <doi:10.1177/10464964221118674>.

Supports the analysis of oceanographic data recorded by Argo autonomous drifting profiling floats. Functions are provided to (a) download and cache data files, (b) subset data in various ways, (c) handle quality-control flags and (d) plot the results according to oceanographic conventions. A shiny app is provided for easy exploration of datasets. The package is designed to work well with the oce package, providing a wide range of processing capabilities that are particular to oceanographic analysis. See Kelley, Harbin, and Richards (2021) <doi:10.3389/fmars.2021.635922> for more on the scientific context and applications.

Inference of protein complex states from quantitative proteomics data. The package takes information on known stable protein interactions (i.e. protein components of the same complex) and assesses how protein quantitative ratios change between different conditions. It reports protein pairs for which relative protein quantities to each other have been significantly altered in the tested condition.

This package provides tools for downloading hourly averages, daily maximums and minimums from each of the pollution, wind, and temperature measuring stations or geographic zones in the Mexico City metro area. The package also includes the locations of each of the stations and zones. See <http://aire.cdmx.gob.mx/> for more information.

Wraps the Ace editor in a HTML widget. The Ace editor has support for many languages. It can be opened in the viewer pane of RStudio', and this provides a second source editor.

Consider autoregressive model of order p where the distribution function of innovation is unknown, but innovations are independent and symmetrically distributed. The package contains a function named ARMDE which takes X (vector of n observations) and p (order of the model) as input argument and returns minimum distance estimator of the parameters in the model.

This package provides tools for validating, generating, reviewing, reporting, and visualising assessment item generation workflows. The package supports tabular item-bank templates, item-bank validation, Python'-backed agentic generation workflows, multimodal diagram generation, quality summaries, and HTML reporting. External artificial intelligence services and related API calls require user-supplied credentials and are not called during package checks. The workflow is informed by automatic item generation methods described by Gierl and Haladyna (2013, ISBN:9780415897518) and evidence-centered assessment design described by Mislevy et al. (2003) <doi:10.1002/j.2333-8504.2003.tb01908.x>.

Exclusion-based parentage assignment is essential for studies in biodiversity conservation and breeding programs - Kang Huang, Rui Mi, Derek W Dunn, Tongcheng Wang, Baoguo Li, (2018), <doi:10.1534/genetics.118.301592>. The tool compares multilocus genotype data of potential parents and offspring, identifying likely parentage relationships while accounting for genotyping errors, missing data, and duplicate genotypes. acoRn includes two algorithms: one generates synthetic genotype data based on user-defined parameters, while the other analyzes existing genotype data to identify parentage patterns. The package is versatile, applicable to diverse organisms, and offers clear visual outputs, making it a valuable resource for researchers.

Estimating and analyzing auto regressive integrated moving average (ARIMA) models. The primary function in this package is arima(), which fits an ARIMA model to univariate time series data using a random restart algorithm. This approach frequently leads to models that have model likelihood greater than or equal to that of the likelihood obtained by fitting the same model using the arima() function from the stats package. This package enables proper optimization of model likelihoods, which is a necessary condition for performing likelihood ratio tests. This package relies heavily on the source code of the arima() function of the stats package. For more information, please see Jesse Wheeler and Edward L. Ionides (2025) <doi:10.1371/journal.pone.0333993>.

Several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697). Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas triangulation code which is part of Akimas Fortran code. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids. Please note that most of the functions are now also covered in package interp, which is a re-implementation from scratch under a free license.

Extract and process bird sightings records from eBird (<http://ebird.org>), an online tool for recording bird observations. Public access to the full eBird database is via the eBird Basic Dataset (EBD; see <http://ebird.org/ebird/data/download> for access), a downloadable text file. This package is an interface to AWK for extracting data from the EBD based on taxonomic, spatial, or temporal filters, to produce a manageable file size that can be imported into R.

Create APA style text from analyses for use within R Markdown documents. Descriptive statistics, confidence intervals, and cell sizes are reported.

Parentage assignment package. Parentage assignment is performed based on observed average Mendelian transmission probability distributions or Exclusion. The main functions of this package are the function APIS_2n(), APIS_3n() and launch_APIShiny(), which perform parentage assignment.

This package provides a weekly summary of Hass Avocado sales for the contiguous US from January 2017 through December 20204. See the package website for more information, documentation, and examples. Data source: Haas Avocado Board <https://hassavocadoboard.com/category-data/>.

You can use this package to create custom pipeline badges in a standard svg format. This is useful for a company to use internally, where it may not be possible to create badges through external providers. This project was inspired by the anybadge library in python.

Easy-to-use tools for performing complex queries on avidaDB', a semantic database that stores genomic and transcriptomic data of self-replicating computer programs (known as digital organisms) that mutate and evolve within a user-defined computational environment.

Assess the sensitivity of a Bayesian model (fitted using Stan via rstan', brms', or cmdstanr') to the specification of its likelihood and priors. Users provide a series of alternate sampling specifications, and the package uses Pareto-smoothed importance sampling (PSIS) to estimate posterior quantities of interest under each specification, without needing to refit the model. Methods are based on Vehtari, Simpson, Gelman, Yao, and Gabry (2024) <doi:10.48550/arXiv.1507.02646>.

Adaptive wavelet lifting transforms for signal denoising using optimal local neighbourhood regression, from Nunes et al. (2006) <doi:10.1007/s11222-006-6560-y>.

Create American Psychological Association Style, Seventh Edition documents. Format numbers and text consistent with APA style. Create tables that comply with APA style by extending flextable functions.

This package provides methods to analyse the stability of non-deterministic prediction models. Prediction stability is quantified either as data-based prediction stability (phi) or as model-based prediction stability (psi). The package implements measures for categorical, ordinal, and metric predictions based on repeated model fitting and corresponding predictions. Methods are based on Lange et al. (2025) <doi:10.1186/s12859-025-06097-1>.