Shinohara (2014) <doi:10.1016/j.nicl.2014.08.008> introduced WhiteStripe', an intensity-based normalization of T1 and T2 images, where normal appearing white matter performs well, but requires segmentation. This method performs white matter mean and standard deviation estimates on data that has been rigidly-registered to the MNI template and uses histogram-based methods.

This package provides two functions frameableWidget()', and frameWidget()'. The frameableWidget() is used to add extra code to a htmlwidget which allows is to be rendered correctly inside a responsive iframe'. The frameWidget() is a htmlwidget which displays content of another htmlwidget inside a responsive iframe'. These functions allow for easier embedding of htmlwidgets in content management systems such as wordpress', blogger etc. They also allow for separation of widget content from main HTML content where CSS of the main HTML could interfere with the widget.

Builds a joint probabilistic forecast across series and horizons using adaptive copulas (Gaussian/t) with shrinkage-repaired correlations. At the low level it calls a probabilistic mixer per series and horizon, which backtests several simple predictors, predicts next-window Continuous Ranked Probability Score (CRPS), and converts those scores into softmax weights to form a calibrated mixture (r/q/p/dfun). The mixer blends eight simple predictors: a naive predictor that wraps the last move in a PERT distribution; an arima predictor using auto.arima for one-step forecasts; an Exponentially Weighted Moving Average (EWMA) gaussian predictor with mean/variance under a Gaussian; a historical bootstrap predictor that resamples past horizon-aligned moves; a drift residual bootstrap predictor combining linear trend with bootstrapped residuals; a volatility-scaled naive predictor centering on the last move and scaling by recent volatility; a robust median mad predictor using median/MAD with Laplace or Normal shape; and a shrunk quantile predictor that fits a few quantile regressions over time and interpolates to a full predictive. The function then couples the per-series mixtures on a common transform (additive/multiplicative/log-multiplicative), simulates coherent draws, and returns both transformed- and level-scale samplers and summaries.

Create, store, read and manage structured collections of datasets and other objects using a workspace', then bundle it into a compressed archive. Using open and interoperable formats makes it possible to exchange bundled data from R to other languages such as Python or Julia'. Multiple formats are supported Parquet', JSON', yaml', spatial data and raster data are supported.

Serves for rendering MS Word documents with R inline code and inserting tables and plots.

The weighted ensemble method is a valuable approach for combining forecasts. This algorithm employs several optimization techniques to generate optimized weights. This package has been developed using algorithm of Armstrong (1989) <doi:10.1016/0024-6301(90)90317-W>.

The BACON algorithms are methods for multivariate outlier nomination (detection) and robust linear regression by Billor, Hadi, and Velleman (2000) <doi:10.1016/S0167-9473(99)00101-2>. The extension to weighted problems is due to Beguin and Hulliger (2008) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X200800110616>; see also <doi:10.21105/joss.03238>.

Wavelet routines that calculate single sets of wavelet multiple regressions and correlations, and cross-regressions and cross-correlations from a multivariate time series. Dynamic versions of the routines allow the wavelet local multiple (cross-)regressions and (cross-)correlations to evolve over time.

Organizational framework for web development in R including functions to serve static and dynamic content via HTTP methods, includes the html5 package to create HTML pages, and offers other utility functions for common tasks related to web development.

Book is "Linear Mixed Models: A Practical Guide Using Statistical Software" published in 2006 by Chapman Hall / CRC Press.

Tool-set of modules for creating web-based applications that use plot based strategies to visualize and analyze multi-omics data. This package utilizes the shiny and plotly frameworks to provide a user friendly dashboard for interactive plotting.

An R interface to the WebAIM WAVE accessibility evaluation API <https://wave.webaim.org/api/>. This package provides tools for analyzing web pages for accessibility issues, generating reports, and comparing accessibility across multiple websites.

Easily collect walk scores, bike scores, and transit scores (where available) from the Walk Score API <https://www.walkscore.com/professional/api.php>, a proprietary API that assigns locations a walkability score between 0 and 100.

This package provides estimation and inference for win statistics in cluster-randomized trials with prioritized (hierarchical) composite outcomes. Supported summaries include the win ratio, win odds, net benefit, and desirability of outcome ranking (DOOR), with variance estimation and testing procedures that account for within-cluster correlation. Methods are described in the accompanying manuscript (2026) <doi:10.48550/arXiv.2604.18341>.

Perform the calculation of W-test, diagnostic checking, calculate minor allele frequency (MAF) and odds ratio.

This package provides a multivariate weather generator for daily climate variables based on weather-states (Flecher et al. (2010) <doi:10.1029/2009WR008098>). It uses a Markov chain for modeling the succession of weather states. Conditionally to the weather states, the multivariate variables are modeled using the family of Complete Skew-Normal distributions. Parameters are estimated on measured series. Must include the variable Rain and can accept as many other variables as desired.

The wavelet-based quantile mapping (WQM) technique is designed to correct biases in spatio-temporal precipitation forecasts across multiple time scales. The WQM method effectively enhances forecast accuracy by generating an ensemble of precipitation forecasts that account for uncertainties in the prediction process. For a comprehensive overview of the methodologies employed in this package, please refer to Jiang, Z., and Johnson, F. (2023) <doi:10.1029/2022EF003350>. The package relies on two packages for continuous wavelet transforms: WaveletComp', which can be installed automatically, and wmtsa', which is optional and available from the CRAN archive <https://cran.r-project.org/src/contrib/Archive/wmtsa/>. Users need to manually install wmtsa from this archive if they prefer to use wmtsa based decomposition.

This package creates interactive web maps using the JavaScript Leaflet library with base layers of The National Map ('TNM'). TNM services provide access to base geospatial information that describes the landscape of the United States and its territories. This package is dependent on, and intended to be used with, the leaflet package.

This package implements the diagnostic "theta" developed in Poetscher and Preinerstorfer (2020) "How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?" <doi:10.48550/arXiv.2005.04089>, which appeared as <doi:10.1017/S0266466622000184> in Econometric Theory , Volume 39 , Issue 4 , August 2023 , pp. 789 - 847. The diagnostic "theta" can be used to detect and weed out bootstrap-based procedures that provably have size equal to one for a given testing problem. The implementation covers a large variety of bootstrap-based procedures, cf. the above mentioned article for details. A function for computing bootstrap p-values is provided.

This package performs a sensitivity analysis using weighted rank tests in observational studies with I blocks of size J; see Rosenbaum (2024) <doi:10.1080/01621459.2023.2221402>. The package can perform adaptive inference in block designs; see Rosenbaum (2012) <doi:10.1093/biomet/ass032>. The package can increase design sensitivity using the conditioning tactic in Rosenbaum (2025) <doi:10.1093/jrsssb/qkaf007>. The main functions are wgtRank(), wgtRankCI(), wgtRanktt() and wgtRankC().

Utilities for using a probability sample to reweight prevalence estimates calculated from the All of Us research program. Weighted estimates will still not be representative of the general U.S. population. However, they will provide an early indication for how unweighted estimates may be biased by the sampling bias in the All of Us sample.

Generate wordsearch and crossword puzzles using custom lists of words (and clues). Make them easy or hard, and print them to solve offline with paper and pencil!

Standardizes and reconciles scientific plant names against a World Checklist of Vascular Plants ('WCVP')-style taxonomic backbone. The package parses names into taxonomic components and applies staged exact and fuzzy matching for binomial and trinomial inputs, including infraspecific rank-aware checks. It also returns accepted-name context and row-level matching flags to support reproducible, auditable preprocessing for downstream biodiversity, spatial, and trait analyses. A user-supplied backbone can be passed through target_df'; when the optional companion package wcvpdata is installed, its default checklist can also be used.

This dataset was collected using a new four-arm within-study comparison design. The study aimed to examine the impact of a mathematics training intervention and a vocabulary study session on post-test scores in mathematics and vocabulary, respectively. The innovative four-arm within-study comparison design facilitates both experimental and quasi-experimental identification of average causal effects.