Root Expected Proportion Squared Difference (REPSD) is a nonparametric differential item functioning (DIF) method that (a) allows practitioners to explore for DIF related to small, fine-grained focal groups of examinees, and (b) compares the focal group directly to the composite group that will be used to develop the reported test score scale. Using your provided response matrix with a column that identifies focal group membership, this package provides the REPSD values, a simulated null distribution of possible REPSD values, and the simulated p-values identifying items possibly displaying DIF without requiring enormous sample sizes.

This package provides tools for linear, nonlinear and nonparametric regression and classification. Novel graphical methods for assessment of parametric models using nonparametric methods. One vs. All and All vs. All multiclass classification, optional class probabilities adjustment. Nonparametric regression (k-NN) for general dimension, local-linear option. Nonlinear regression with Eickert-White method for dealing with heteroscedasticity. Utilities for converting time series to rectangular form. Utilities for conversion between factors and indicator variables. Some code related to "Statistical Regression and Classification: from Linear Models to Machine Learning", N. Matloff, 2017, CRC, ISBN 9781498710916.

An R package for estimating conditional multivariate reference regions. The reference region is non parametrically estimated using a kernel density estimator. Covariates effects on the multivariate response means vector and variance-covariance matrix, thus on the region shape, are estimated by flexible additive predictors. Continuous covariates non linear effects might be estimated using penalized splines smoothers. Confidence intervals for the covariates estimated effects might be derived from bootstrap resampling. Kernel density bandwidth can be estimated with different methods, including a method that optimize the region coverage. Numerical, and graphical, summaries can be obtained by the user in order to evaluate reference region performance with real data. Full mathematical details can be found in <doi:10.1002/sim.9163> and <doi:10.1007/s00477-020-01901-1>.

Assemble the panels of computerized adaptive multistage testing by the bottom-up and the top-down approach, and simulate the administration of the assembled panels. The full documentation and tutorials are at <https://github.com/xluo11/Rmst>. Reference: Luo and Kim (2018) <doi:10.1111/jedm.12174>.

Load data from Yandex Direct API V5 <https://yandex.ru/dev/direct/doc/dg/concepts/about-docpage> into R. Provide function for load lists of campaings, ads, keywords and other objects from Yandex Direct account. Also you can load statistic from API Reports Service <https://yandex.ru/dev/direct/doc/reports/reports-docpage>. And allows keyword bids management.

This package provides tools to fit and simulate realizations from relational event models.

This package provides functions to facilitate inference on the relative importance of predictors in a linear or generalized linear model, and a couple of useful Tcl/Tk widgets.

R packages for genetics research.

Microbenchmarks for determining the run time performance of aspects of the R programming environment and packages relevant to high-performance computation. The benchmarks are divided into three categories: dense matrix linear algebra kernels, sparse matrix linear algebra kernels, and machine learning functionality.

Data driven approach for robust regression estimation in homoscedastic and heteroscedastic context. See Wang et al. (2007), <doi:10.1198/106186007X180156> regarding homoscedastic framework.

Build powerful pivot tables (aka Pivot Grid, Pivot Chart, Cross-Tab) and dynamically slice & dice / drag n drop your data. rpivotTable is a wrapper of pivottable', a powerful open-source Pivot Table library implemented in JavaScript by Nicolas Kruchten. Aligned to pivottable v2.19.0.

Calculate the flow of particles between polygons by two integration methods: integration by a cubature method and integration on a grid of points. Annie Bouvier, Kien Kieu, Kasia Adamczyk and Herve Monod (2009) <doi:10.1016/j.envsoft.2008.11.006>.

This package provides a collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.

Work with the PhyloPic Web Service (<http://api-docs.phylopic.org/v2/>) to fetch silhouette images of organisms. Includes functions for adding silhouettes to both base R plots and ggplot2 plots.

Compute time-dependent Incident/dynamic accuracy measures (ROC curve, AUC, integrated AUC )from censored survival data under proportional or non-proportional hazard assumption of Heagerty & Zheng (Biometrics, Vol 61 No 1, 2005, PP 92-105).

Visualizing crystal structures and selected area electron diffraction (SAED) patterns. It provides functions cry_demo() and dp_demo() to load a file in CIF (Crystallographic Information Framework) formats and display crystal structures and electron diffraction patterns. The function dp_demo() also performs simple simulation of powder X-ray diffraction (PXRD) patterns, and the results can be saved to a file in the working directory. The package has been tested on several platforms, including Linux on Crostini with a Coreâ ¢ m3-8100Y Chromebook, I found that even on this low-powered platform, the performance was acceptable. T. Hanashima (2001) <https://www2.kek.jp/imss/pf/tools/sasaki/sinram/sinram.html> Todd Helmenstine (2019) <https://sciencenotes.org/molecule-atom-colors-cpk-colors/> Wikipedia contributors (2023) <https://en.wikipedia.org/w/index.php?title=Atomic_radius&oldid=1179864711>.

Modeling and plotting functions for Reliability Growth Analysis (RGA). Models include the Duane (1962) <doi:10.1109/TA.1964.4319640>, Non-Homogeneous Poisson Process (NHPP) by Crow (1975) (No. AMSAATR138), Piecewise Weibull NHPP by Guo et al. (2010) <doi:10.1109/RAMS.2010.5448029>, and Piecewise Weibull NHPP with Change Point Detection based on the segmented package by Muggeo (2024) <https://cran.r-project.org/package=segmented>.

This package provides functions to retrieve data and metadata from providers that disseminate data by means of SDMX web services. SDMX (Statistical Data and Metadata eXchange) is a standard that has been developed with the aim of simplifying the exchange of statistical information. More about the SDMX standard and the SDMX Web Services can be found at: <https://sdmx.org>.

Hydrologic modelling system is an object oriented tool for simulation and analysis of hydrologic events. The package proposes functions and methods for construction, simulation, visualization, and calibration of a hydrologic model.

This package provides access to and analysis of data from "The Red Book of Endemic Plants of Peru" (León, B., Roque, J., Ulloa, C., Jorgensen, P.M., Pitman, N., Cano, A. 2006) <doi:10.15381/rpb.v13i2.1782>. This package offers comprehensive taxonomic, geographic, and conservation information about Peru's endemic plant species. It includes functions to verify species inclusion, obtain updated taxonomic details, and explore the dataset.

The Nearest Neighbor Descent method for finding approximate nearest neighbors by Dong and co-workers (2010) <doi:10.1145/1963405.1963487>. Based on the Python package PyNNDescent <https://github.com/lmcinnes/pynndescent>.

Provide function for work with AcademyOcean API <https://academyocean.com/api>.

Upload R data.frame to Arm Treasure Data, see <https://www.treasuredata.com/>. You can execute database or table handling for resources on Arm Treasure Data.

This package provides a Tidy implementation of grouping sets', rollup and cube - extensions of the group_by clause that allow for computing multiple group_by clauses in a single statement. For more detailed information on these functions, please refer to "Enhanced Aggregation, Cube, Grouping and Rollup" <https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup>.