This package provides a graphical user interface to the IsoplotR package for radiometric geochronology. The GUI runs in an internet browser and can either be used offline, or hosted on a server to provide online access to the IsoplotR toolbox.

This package provides functions read a dataframe containing one or more International Classification of Diseases Tenth Revision codes per subject. They return original data with injury categorizations and severity scores added.

This package provides statistical workflows used in the evaluation of in vitro diagnostic reagents. Facilities include method comparison, commutability assessment, Bland-Altman and receiver operating characteristic analysis, qualitative agreement, C5 and C95 estimation, precision and variance-component analysis, linearity, interference, dilution and spiking studies, high-dose hook assessment, measurement uncertainty, reference-material bias, reference intervals, stability studies, quality-control charts, curve fitting, analytical sensitivity, outlier and normality assessment, and sample-size calculations. For methodological details, see Bland and Altman (1986) <doi:10.1016/S0140-6736(86)90837-8>, Passing and Bablok (1983) <doi:10.1515/cclm.1983.21.11.709>, Linnet (1993) <doi:10.1093/clinchem/39.3.424>, Hawkins and Kraker (2026) <doi:10.1093/jalm/jfaf183>, Hanley and McNeil (1982) <doi:10.1148/radiology.143.1.7063747>, Horn et al. (1998) <doi:10.1093/clinchem/44.3.622>, Westgard et al. (1981) <doi:10.1093/clinchem/27.3.493>, and Lu et al. (2016) <doi:10.1515/ijb-2015-0039>.

We provide an R tool for teaching in Social Sciences. It allows the computation of index numbers. It is a measure of the evolution of a fixed magnitude for only a product of for several products. It is very useful in Social Sciences. Among others, we obtain simple index numbers (in chain or in serie), index numbers for not only a product or weighted index numbers as the Laspeyres index (Laspeyres, 1864), the Paasche index (Paasche, 1874) or the Fisher index (Lapedes, 1978).

This package provides user tokens for ICES web services that require authentication and authorization. Web services covered by this package are ICES VMS database, the ICES DATSU web services, and the ICES SharePoint site <https://www.ices.dk/data/tools/Pages/WebServices.aspx>.

This package provides a R package to find the IP addresses which are used as VPN anonymizer, open proxies, web proxies and Tor exits. The package lookup the proxy IP address from IP2Proxy BIN Data file. You may visit <https://lite.ip2location.com> for free database download.

Quick indexation of any type of vector or of any combination of those. Indexation turns a vector into an integer vector going from 1 to the number of unique elements. Indexes are important building blocks for many algorithms. The method is described at <https://github.com/lrberge/indexthis/>.

Interface to the OpenGWAS database API <https://api.opengwas.io/api/>. Includes a wrapper to make generic calls to the API, plus convenience functions for specific queries.

This package implements information-theoretic measures to explore variable interactions, including KSG mutual information estimation for continuous variables from Kraskov et al. (2004) <doi:10.1103/PhysRevE.69.066138>, knockoff conditional mutual information described in Zhang & Chen (2025) <doi:10.1126/sciadv.adu6464>, synergistic-unique-redundant decomposition introduced by Martinez-Sanchez et al. (2024) <doi:10.1038/s41467-024-53373-4>, allowing detection of complex and diverse relationships among variables.

Computes and decomposes Gini, Bonferroni and Zenga 2007 point and synthetic concentration indexes. Decompositions are intended: by sources, by subpopulations and by sources and subpopulations jointly. References, Zenga M. M.(2007) <doi:10.1400/209575> Zenga M. (2015) <doi:10.1400/246627> Zenga M., Valli I. (2017) <doi:10.26350/999999_000005> Zenga M., Valli I. (2018) <doi:10.26350/999999_000011>.

The general workflow of most imputation methods is quite similar. The aim of this package is to provide parts of this general workflow to make the implementation of imputation methods easier. The heart of an imputation method is normally the used model. These models can be defined using the parsnip package or customized specifications. The rest of an imputation method are more technical specification e.g. which columns and rows should be used for imputation and in which order. These technical specifications can be set inside the imputation functions.

This package provides low-level access to the International Monetary Fund Statistical Data and Metadata eXchange ('SDMX') 3.0 API, available at <https://data.imf.org/>, and a concise workflow for discovering datasets, inspecting dimensions, and downloading observations as tidy data frames.

Computes the key metrics for assessing the performance of a liquidity provider (LP) position in a weighted multi-asset Automated Market Maker (AMM) pool. Calculates the nominal and percentage impermanent loss (IL) by comparing the portfolio value inside the pool (based on the weighted geometric mean of price ratios) against the value of simply holding the assets outside the pool (based on the weighted arithmetic mean). The primary function, `impermanent_loss()`, incorporates the effect of earned trading fees to provide the LP's net profit and loss relative to a holding strategy, using a methodology derived from Tiruviluamala, N., Port, A., and Lewis, E. (2022) <doi:10.48550/arXiv.2203.11352>.

Estimates the intraclass correlation coefficient for trajectory data using a matrix of distances between trajectories. The distances implemented are the extended Hausdorff distances (Min et al. 2007) <doi:10.1080/13658810601073315> and the discrete Fréchet distance (Magdy et al. 2015) <doi:10.1109/IntelCIS.2015.7397286>.

This package provides a suite of functions for conducting and interpreting analysis of statistical interaction in regression models that was formerly part of the jtools package. Functionality includes visualization of two- and three-way interactions among continuous and/or categorical variables as well as calculation of "simple slopes" and Johnson-Neyman intervals (see e.g., Bauer & Curran, 2005 <doi:10.1207/s15327906mbr4003_5>). These capabilities are implemented for generalized linear models in addition to the standard linear regression context.

Carries out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics. See Kang, Jiang, Zhao, and Small (2020) <http://pages.cs.wisc.edu/~hyunseung/> for details.

This package performs exploratory data analysis and variable screening for binary classification models using weight-of-evidence (WOE) and information value (IV). In order to make the package as efficient as possible, aggregations are done in data.table and creation of WOE vectors can be distributed across multiple cores. The package also supports exploration for uplift models (NWOE and NIV).

An implementation of the Canny Edge Detector for detecting edges in images. The package provides an interface to the algorithm available at <https://github.com/Neseb/canny>.

This package contains techniques for mining large and high-dimensional data sets by using the concept of Intrinsic Dimension (ID). Here the ID is not necessarily an integer. It is extended to fractal dimensions. And the Morisita estimator is used for the ID estimation, but other tools are included as well.

It provides multiple functions that are useful for ecological research and teaching statistics to ecologists. It is based on data analysis courses offered at the Instituto de Ecologà a AC (INECOL). For references and published evidence see, Manrique-Ascencio, et al (2024) <doi:10.1111/gcb.17282>, Manrique-Ascencio et al (2024) <doi:10.1111/plb.13683>, Ruiz-Guerra et al(2017) <doi:10.17129/botsci.812>, Juarez-Fragoso et al (2024) <doi:10.1007/s10980-024-01809-z>, Papaqui-Bello et al (2024) <doi:10.13102/sociobiology.v71i2.10503>.

These datasets and functions accompany Wolfe and Schneider (2017) - Intuitive Introductory Statistics (ISBN: 978-3-319-56070-0) <doi:10.1007/978-3-319-56072-4>. They are used in the examples throughout the text and in the end-of-chapter exercises. The datasets are meant to cover a broad range of topics in order to appeal to the diverse set of interests and backgrounds typically present in an introductory Statistics class.

Fits Bayesian hierarchical models of vaccine coverage by location, birth cohort, and age. Observations of vaccination status (which may span cohorts, ages, and doses) are used to fit a latent survival-style process model that decomposes coverage into a lifetime propensity to vaccinate and a time-varying force of vaccination. Hierarchical spatial structure (e.g., state, county, school) supports partial pooling via random effects. Models are implemented in Stan and fit via rstan'. Provides helpers to validate user-supplied input data, and to predict coverage from fitted models.

This package provides a tiny parser to extract mass spectra data and metadata table of mass spectrometry acquisition properties from mzML, mzXML and netCDF files introduced in <doi:10.1021/acs.jproteome.2c00120>.

The 14th generation International Geomagnetic Reference Field (IGRF). A standard spherical harmonic representation of the Earth's main field.