Psychometric analysis and scoring of judgment data using polytomous Item-Response Theory (IRT) models, as described in Myszkowski and Storme (2019) <doi:10.1037/aca0000225> and Myszkowski (2021) <doi:10.1037/aca0000287>. A function is used to automatically compare and select models, as well as to present a variety of model-based statistics. Plotting functions are used to present category curves, as well as information, reliability and standard error functions.

Shared parameter models for the joint modeling of longitudinal and time-to-event data.

Approximate joint-inclusion probabilities in Unequal Probability Sampling, or compute Monte Carlo approximations of the first and second-order inclusion probabilities of a general sampling design as in Fattorini (2006) <doi:10.1093/biomet/93.2.269>.

Estimate risk caused by two extreme and dependent forcing variables using bivariate extreme value models as described in Zheng, Westra, and Sisson (2013) <doi:10.1016/j.jhydrol.2013.09.054>; Zheng, Westra and Leonard (2014) <doi:10.1002/2013WR014616>; Zheng, Leonard and Westra (2015) <doi:10.2166/hydro.2015.052>.

The jscore() function in the package calculates the J-Score metric between two clustering assignments. The score is designed to address some problems with existing common metrics such as problem of matching. The details of J-score is described in Ahmadinejad and Liu. (2021) <arXiv:2109.01306>.

Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and longitudinal data in the presence of heterogeneous within-subject variability, proposed by Li and colleagues (2023) <arXiv:2301.06584>. The proposed method models the within-subject variability of the biomarker and associates it with the risk of the competing risks event. The time-to-event data is modeled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates. The longitudinal outcome is modeled using a mixed-effects location and scale model. The association is captured by shared random effects. The model is estimated using an Expectation Maximization algorithm.

Individual based simulations of hybridizing populations, where the accumulation of junctions is tracked. Furthermore, mathematical equations are provided to verify simulation outcomes. Both simulations and mathematical equations are based on Janzen (2018, <doi:10.1101/058107>) and Janzen (2022, <doi:10.1111/1755-0998.13519>).

This package provides tools to explore and summarize relationship patterns between variables across one or multiple datasets. The package relies on efficient sampling strategies to estimate pairwise associations and supports quick exploratory data analysis for large or heterogeneous data sources.

This package creates interactive trees that can be included in Shiny apps and R markdown documents. A tree allows to represent hierarchical data (e.g. the contents of a directory). Similar to the shinyTree package but offers more features and options, such as the grid extension, restricting the drag-and-drop behavior, and settings for the search functionality. It is possible to attach some data to the nodes of a tree and then to get these data in Shiny when a node is selected. Also provides a Shiny gadget allowing to manipulate one or more folders, and a Shiny module allowing to navigate in the server side file system.

This package provides functions to access data from public RESTful APIs including Nager.Date', World Bank API', and REST Countries API', retrieving real-time or historical data related to Japan, such as holidays, economic indicators, and international demographic and geopolitical indicators. Additionally, the package includes one of the largest curated collections of open datasets focused on Japan, covering topics such as natural disasters, economic production, vehicle industry, air quality, demographics, and administrative divisions. The package supports reproducible research and teaching by integrating reliable international APIs and structured datasets from public, academic, and government sources. For more information on the APIs, see: Nager.Date <https://date.nager.at/Api>, World Bank API <https://datahelpdesk.worldbank.org/knowledgebase/articles/889392>, and REST Countries API <https://restcountries.com/>.

Leverages the yum package to implement a YAML ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https://yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.

Minimal and memory efficient implementation of the junction tree algorithm using the Lauritzen-Spiegelhalter scheme; S. L. Lauritzen and D. J. Spiegelhalter (1988) <https://www.jstor.org/stable/2345762?seq=1>. The jti package is part of the paper <doi:10.18637/jss.v111.i02>.

This package provides method used to check whether data have outlier in efficiency measurement of big samples with data envelopment analysis (DEA). In this jackstrap method, the package provides two criteria to define outliers: heaviside and k-s test. The technique was developed by Sousa and Stosic (2005) "Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers." <doi:10.1007/s11123-005-4702-4>.

The Jalaali calendar, also known as the Persian or Solar Hijri calendar, is the official calendar of Iran and Afghanistan. It starts on Nowruz, the spring equinox, and follows an astronomical system for determining leap years. Each year consists of 365 or 366 days, divided into 12 months. This package provides functions for converting dates between the Jalaali and Gregorian calendars. The conversion calculations are based on the work of Kazimierz M. Borkowski (1996) (<doi:10.1007/BF00055188>), who used an analytical model of Earth's motion to compute equinoxes from AD 550 to 3800 and determine leap years based on Tehran time.

This package provides functions and data to reproduce all plots in the book "Practical Smoothing. The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950).

Download and post process the infectious disease case data from Japan Institute for Health Security. Also the package included ready-to-analyse datasets. See the data source website for further details <https://id-info.jihs.go.jp/>.

This package provides a RStudio addin to send some JavaScript code to the V8 console. The user can send an entire JavaScript file or only some selected lines. This is useful to test the code.

Read Japanese city codes (<https://www.e-stat.go.jp/municipalities/cities>) to get city and prefecture names, or convert to city codes at different points in time. In addition, it merges or splits wards of designated cities and gets all city codes at a specific point in time.

An implementation of fast cluster-based permutation analysis (CPA) for densely-sampled time data developed in Maris & Oostenveld, 2007 <doi:10.1016/j.jneumeth.2007.03.024>. Supports (generalized, mixed-effects) regression models for the calculation of timewise statistics. Provides both a wholesale and a piecemeal interface to the CPA procedure with an emphasis on interpretability and diagnostics. Integrates Julia libraries MixedModels.jl and GLM.jl for performance improvements, with additional functionalities for interfacing with Julia from R powered by the JuliaConnectoR package.

Automatic disaggregation of small-area population estimates by demographic groups (e.g., age, sex, race, marital status, educational level, etc) along with the estimates of uncertainty, using advanced Bayesian statistical modelling approaches based on integrated nested Laplace approximation (INLA) Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x> and stochastic partial differential equation (SPDE) methods Lindgren et al. (2011) <doi:10.1111/j.1467-9868.2011.00777.x>. The package implements hierarchical Bayesian modeling frameworks for small area estimation as described in Leasure et al. (2020) <doi:10.1073/pnas.1913050117> and Nnanatu et al. (2025) <doi:10.1038/s41467-025-59862-4>.

This package provides tools are provided to streamline Bayesian analyses in JAGS using the jagsUI package. Included are functions for extracting output in simpler format, functions for streamlining assessment of convergence, and functions for producing summary plots of output. Also included is a function that provides a simple template for running JAGS from R'. Referenced materials can be found at <DOI:10.1214/ss/1177011136>.

This package implements an S4 distribution system and estimation methods for parameters of common distribution families. The common d, p, q, r function family for each distribution is enriched with the ll, e, and v counterparts, computing the log-likelihood, performing estimation, and calculating the asymptotic variance - covariance matrix, respectively. Parameter estimation is performed analytically whenever possible.

Set of common functions used for manipulating colors, detecting and interacting with RStudio', modeling, formatting, determining users operating system, feature scaling, and more!

This package provides a GUI interface for automating data extraction from multiple images containing scatter and bar plots, semi-automated tools to tinker with extraction attempts, and a fully-loaded point-and-click manual extractor with image zoom, calibrator, and classifier. Also provides detailed and R-independent extraction reports as fully-embedded .html records.