Decomposition of income inequality by groups formed of individuals possessing similar characteristics (e.g., sex, education, age) and their income sources at the same time. Decomposition of the Theil index is based on Giammatteo, M. (2007) <https://www.lisdatacenter.org/wps/liswps/466.pdf>. Decomposition of the squared coefficient of variation is based on Garcia-Penalosa, C., & Orgiazzi, E. (2013) <doi:10.1111/roiw.12054>.

This package provides methods for testing the equality of dependent intraclass correlation coefficients (ICCs) estimated using linear mixed-effects models. Several of the implemented approaches are based on the work of Donner and Zou (2002) <doi:10.1111/1467-9884.00324>.

Density, spectral density, and regression estimation using infinite order flat-top kernels.

An easy way to work with census, survey, and geographic data provided by IPUMS in R. Generate and download data through the IPUMS API and load IPUMS files into R with their associated metadata to make analysis easier. IPUMS data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from the IPUMS website <https://www.ipums.org>.

Facilitates access to the International Union for Conservation of Nature (IUCN) Red List of Threatened Species, a comprehensive global inventory of species at risk of extinction. This package streamlines the process of determining conservation status by matching species names with Red List data, providing tools to easily query and retrieve conservation statuses. Designed to support biodiversity research and conservation planning, this package relies on data from the iucnrdata package, available on GitHub <https://github.com/PaulESantos/iucnrdata>. To install the data package, use pak::pak('PaulESantos/iucnrdata').

Uses data and researcher's beliefs on measurement error and instrumental variable (IV) endogeneity to generate the space of consistent beliefs across measurement error, instrument endogeneity, and instrumental relevance for IV regressions. Package based on DiTraglia and Garcia-Jimeno (2020) <doi:10.1080/07350015.2020.1753528>.

This package provides functions for analyzing multiple choice items. These analyses include the convertion of student response into binaty data (correct/incorrect), the computation of the number of corrected responses and grade for each subject, the calculation of item difficulty and discrimination, the computation of the frecuency and point-biserial correlation for each distractor and the graphical analysis of each item.

The digits of the old version (before 2000 year) of Chinese ID Card Number is 15, this package aims to update to the current version of 18 digits. Besides, this package can help check whether the given ID is right or not.

This package implements the standard D-Scoring algorithm (Greenwald, Banaji, & Nosek, 2003) for Implicit Association Test (IAT) data and includes plotting capabilities for exploring raw IAT data.

This package provides functions to calculate the requisite sample size for studies where ICC is the primary outcome. Can also be used for calculation of power. In both cases it allows the user to test the impact of changing input variables by calculating the outcome for several different values of input variables. Based off the work of Zou. Zou, G. Y. (2012). Sample size formulas for estimating intraclass correlation coefficients with precision and assurance. Statistics in medicine, 31(29), 3972-3981.

Four datasets are provided here from the Intendo game Super Jetroid'. It is data from the 2015 year of operation and it comprises a revenue table ('all_revenue'), a daily users table ('users_daily'), a user summary table ('user_summary'), and a table with data on all user sessions ('all_sessions'). These core datasets come in different sizes, and, each of them has a variant that was intentionally made faulty (totally riddled with errors and inconsistencies). This suite of tables is useful for testing with packages that focus on data validation and data documentation.

This package performs Invariant Coordinate Selection (ICS) (Tyler, Critchley, Duembgen and Oja (2009) <doi:10.1111/j.1467-9868.2009.00706.x>) and especially ICS for multivariate outlier detection with application to quality control (Archimbaud, Nordhausen, Ruiz-Gazen (2018) <doi:10.1016/j.csda.2018.06.011>) using a shiny app.

An interval-valued extension of ordinary and simple kriging. Optimization of the function is based on a generalized interval distance. This creates a non-differentiable cost function that requires a differentiable approximation to the absolute value function. This differentiable approximation is optimized using a Newton-Raphson algorithm with a penalty function to impose the constraints. Analyses in the package are driven by the intsp and intgrd classes, which are interval-valued extensions of SpatialPointsDataFrame and SpatialPixelsDataFrame respectively. The package includes several wrappers to functions in the gstat and sp packages.

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>.

Reconstruct birth-year specific probabilities of immune imprinting to influenza A, using the methods of Gostic et al. (2016) <doi:10.1126/science.aag1322>. Plot, save, or export the calculated probabilities for use in your own research. By default, the package calculates subtype-specific imprinting probabilities, but with user-provided frequency data, it is possible to calculate probabilities for arbitrary kinds of primary exposure to influenza A, including primary vaccination and exposure to specific clades, strains, etc.

An R client for the ipbase.com IP Geolocation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://ipbase.com/docs> .

Imputing blockwise missing data by imprecise imputation, featuring a domain-based, variable-wise, and case-wise strategy. Furthermore, the estimation of lower and upper bounds for unconditional and conditional probabilities based on the obtained imprecise data is implemented. Additionally, two utility functions are supplied: one to check whether variables in a data set contain set-valued observations; and another to merge two already imprecisely imputed data. The method is described in a technical report by Endres, Fink and Augustin (2018, <doi:10.5282/ubm/epub.42423>).

This package provides an R version of the InterVA5 software (<http://www.byass.uk/interva/>) for coding cause of death from verbal autopsies. It also provides simple graphical representation of individual and population level statistics.

Infix functions in R are those that comes between its arguments such as %in%, +, and *. These are useful in R programming when manipulating data, performing logical operations, and making new functions. infixit extends the infix functions found in R to simplify frequent tasks, such as finding elements that are NOT in a set, in-line text concatenation, augmented assignment operations, additional logical and control flow operators, and identifying if a number or date lies between two others.

It provides in-place operators for R that are equivalent to +=', -=', *=', /= in C++. Those can be applied on integer|double vectors|matrices. You have also access to sweep operations (in-place).

This package provides a test bench for the comparison of missing data imputation methods in uni-variate time series. Imputation methods are compared using different error metrics. Proposed imputation methods and alternative error metrics can be used.

The inti package is part of the inkaverse project for developing different procedures and tools used in plant science and experimental designs. The mean aim of the package is to support researchers during the planning of experiments and data collection (tarpuy()), data analysis and graphics (yupana()) , and scientific writing. Learn more about the inkaverse project at <https://inkaverse.com/>.

Generalized Odds Rate Hazards (GORH) model is a flexible model of fitting survival data, including the Proportional Hazards (PH) model and the Proportional Odds (PO) Model as special cases. This package fit the GORH model with interval censored data.

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>.