This package provides tools for measuring income and wealth inequality. Computes the Gini coefficient with bootstrap or asymptotic confidence intervals following Davidson (2009) <doi:10.1016/j.jeconom.2008.09.011>, the extended S-Gini family, Theil T and L indices (generalised entropy family), the Atkinson index, the Kolm absolute inequality index, Palma ratio, Hoover index, percentile ratios, and Lorenz curves. Supports between-within group decomposition following Bourguignon (1979) <doi:10.2307/1914138>, income share tabulation, concentration indices for health inequality with Erreygers (2009) correction, Kakwani tax progressivity and Reynolds-Smolensky redistribution indices, Foster-Greer-Thorbecke poverty measures including the Sen index, growth incidence curves following Ravallion and Chen (2003) <doi:10.1016/S0165-1765(02)00205-7>, and Wolfson polarisation. All functions accept optional survey weights and work with data from any source.

Query for enriched data such as country, region, city, latitude & longitude, ZIP code, time zone, Autonomous System, Internet Service Provider, domain, net speed, International direct dialing (IDD) code, area code, weather station data, mobile data, elevation, usage type, address type, advertisement category, fraud score, and proxy data with an IP address. You can also query a list of hosted domain names for the IP address too. This package uses the IP2Location.io API to query this data. To get started with a free API key, sign up here <https://www.ip2location.io/sign-up?ref=1>.

This package implements some item response models for multiple ratings, including the hierarchical rater model, conditional maximum likelihood estimation of linear logistic partial credit model and a wrapper function to the commercial FACETS program. See Robitzsch and Steinfeld (2018) for a description of the functionality of the package. See Wang, Su and Qiu (2014; <doi:10.1111/jedm.12045>) for an overview of modeling alternatives.

Convert files to and from IDX format to vectors, matrices and arrays. IDX is a very simple file format designed for storing vectors and multidimensional matrices in binary format. The format is described on the website from Yann LeCun <http://yann.lecun.com/exdb/mnist/>.

Code to specify, run, and then visualize and analyze the results of Ixodidae (hard-bodied ticks) population and infection dynamics models. Such models exist in the literature, but the source code to run them is not always available. IxPopDyMod provides an easy way for these models to be written and shared.

This package performs estimation, diagnostics, and visualization of conditional marginal effects and group average treatment effects of a treatment on an outcome across different values of a moderator. Optionally integrates with the mlr3extralearners package for additional machine learning backends compatible with the double machine learning estimators. mlr3extralearners is not on CRAN but can be obtained from <https://github.com/mlr-org/mlr3extralearners>.

This package provides a fast (C) implementation of the iterative proportional fitting procedure.

Calculates intraclass correlation coefficient (ICC) for assessing reproducibility of interval-censored data with two repeated measurements (Kovacic and Varnai (2014) <doi:10.1097/EDE.0000000000000139>). ICC is estimated by maximum likelihood from model with one fixed and one random effect (both intercepts). Help in model checking (normality of subjects means and residuals) is provided.

The proportion of cancer cells in solid tumor sample, known as the tumor purity, has adverse impact on a variety of data analyses if not properly accounted for. We develop InfiniumPurify', which is a comprehensive R package for estimating and accounting for tumor purity based on DNA methylation Infinium 450k array data. InfiniumPurify provides functionalities for tumor purity estimation. In addition, it can perform differential methylation detection and tumor sample clustering with the consideration of tumor purities.

Imbalanced domain learning has almost exclusively focused on solving classification tasks, where the objective is to predict cases labelled with a rare class accurately. Such a well-defined approach for regression tasks lacked due to two main factors. First, standard regression tasks assume that each value is equally important to the user. Second, standard evaluation metrics focus on assessing the performance of the model on the most common cases. This package contains methods to tackle imbalanced domain learning problems in regression tasks, where the objective is to predict extreme (rare) values. The methods contained in this package are: 1) an automatic and non-parametric method to obtain such relevance functions; 2) visualisation tools; 3) suite of evaluation measures for optimisation/validation processes; 4) the squared-error relevance area measure, an evaluation metric tailored for imbalanced regression tasks. More information can be found in Ribeiro and Moniz (2020) <doi:10.1007/s10994-020-05900-9>.

An implementation of the International Association for the Properties of Water (IAPWS) Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use and on the releases for viscosity, conductivity, surface tension and melting pressure.

Simple handling of survey data. Smart handling of meta-information like e.g. variable-labels value-labels and scale-levels. Easy access and validation of meta-information. Useage of value labels and values respectively for subsetting and recoding data.

Used in testing if the indirect effect from linear regression mediation analysis is equal to 0. Includes established methods such as the Sobel Test, Joint Significant test (maxP), and tests based off the distribution of the Product or Normal Random Variables. Additionally, this package adds more powerful tests based on Intersection-Union theory. These tests are the S-Test, the ps-test, and the ascending squares test. These new methods are uniformly more powerful than maxP, which is more powerful than Sobel and less anti-conservative than the Product of Normal Random Variables. These methods are explored by Kidd and Lin, (2024) <doi:10.1007/s12561-023-09386-6> and Kidd et al., (2025) <doi:10.1007/s10260-024-00777-7>.

This is an substitute for the %V and %u formats which are not implemented on Windows. In addition, the package offers functions to convert from standard calender format yyyy-mm-dd to and from ISO 8601 week format yyyy-Www-d.

This package provides functions for converting time series of spatial abundance or density data in raster format to vector fields of population movement using the digital image correlation technique. More specifically, the functions in the package compute cross-covariance using discrete fast Fourier transforms for computational efficiency. Vectors in vector fields point in the direction of highest two dimensional cross-covariance. The package has a novel implementation of the digital image correlation algorithm that is designed to detect persistent directional movement when image time series extend beyond a sequence of two raster images.

Boxplots adapted to the happenstance of missing observations where drop-out probabilities can be given by the practitioner or modelled using auxiliary covariates. The paper of "Zhang, Z., Chen, Z., Troendle, J. F. and Zhang, J.(2012) <doi:10.1111/j.1541-0420.2011.01712.x>", proposes estimators of marginal quantiles based on the Inverse Probability Weighting method.

This package provides functions to parse strings with ISO8601 dates, times, and date-times into R-objects. Additionally, there are functions to determine the type of ISO8601 string and to standardise ISO8601 strings.

High resolution mass spectrometry yields often large data sets of spectra from compounds which are not present in available libraries. These spectra need to be annotated and interpreted. InterpretMSSpectrum provides a set of functions to perform such tasks for Electrospray-Ionization and Atmospheric-Pressure-Chemical-Ionization derived data in positive and negative ionization mode.

Deriving isodar-based niche breadth indices from abundance data of two or more habitats, including several methods based on pairwise isodars, multidimensional isodars, and isodar-adjusted inequality.

Data sets and scripts for text examples and exercises in P. Dalgaard (2008), `Introductory Statistics with R', 2nd ed., Springer Verlag, ISBN 978-0387790534.

This package provides a wrapper around the same API <https://app.americansocceranalysis.com/api/v1/__docs__/> that powers the American Soccer Analysis app.

Electricity is not made equal and it vary in its carbon footprint (or carbon intensity) depending on its source. This package enables to access and query data provided by the Carbon Intensity API (<https://carbonintensity.org.uk/>). National Gridâ s Carbon Intensity API provides an indicative trend of regional carbon intensity of the electricity system in Great Britain.

Perform common calculations based on published stable isotope theory, such as calculating carbon isotope discrimination and intrinsic water use efficiency from wood or leaf carbon isotope composition. See Mathias and Hudiburg (2022) in Global Change Biology <doi:10.1111/gcb.16407>.

Interesting igraph datasets from Melanie Walsh's sample social network datasets repository <https://github.com/melaniewalsh/sample-social-network-datasets>.