Estimates high-dimensional multivariate normal copula regression models with the weighted composite likelihood estimating equations in Nikoloulopoulos (2023) <doi:10.1016/j.csda.2022.107654>. It provides autoregressive moving average correlation structures and binary, ordinal, Poisson, and negative binomial regressions.

This package provides tools to quantify how strongly pairs of words attract or repel each other in a text corpus, based on co-occurrence patterns. For each word pair, the phi coefficient (a correlation measure for binary variables) is computed from a document-term matrix and tested for significance, then classified as showing attraction (co-occurring more than chance would predict), repulsion (co-occurring less than chance would predict), or no significant relationship. A full pipeline is provided from raw text to a labeled network visualization. Unlike general-purpose pairwise correlation tools, wordorientation is built specifically for text: it handles tokenization and stopword removal, applies significance-based classification rather than reporting a raw correlation coefficient alone, and produces a ready-to-plot attraction/ repulsion network.

The main functionalities of wrappedtools are: adding backticks to variable names; rounding to desired precision with special case for p-values; selecting columns based on pattern and storing their position, name, and backticked name; computing and formatting of descriptive statistics (e.g. mean±SD), comparing groups and creating publication-ready tables with descriptive statistics and p-values; creating specialized plots for correlation matrices. Functions were mainly written for my own daily work or teaching, but may be of use to others as well.

This package provides insight into how the best hand for a poker game changes based on the game dealt, players who stay in until the showdown and wildcards added to the base game. At this time the package does not support player tactics, so draw poker variants are not included.

This package provides a computationally efficient way of fitting weighted linear fixed effects estimators for causal inference with various weighting schemes. Weighted linear fixed effects estimators can be used to estimate the average treatment effects under different identification strategies. This includes stratified randomized experiments, matching and stratification for observational studies, first differencing, and difference-in-differences. The package implements methods described in Imai and Kim (2017) "When should We Use Linear Fixed Effects Regression Models for Causal Inference with Longitudinal Data?", available at <https://imai.fas.harvard.edu/research/FEmatch.html>.

Applies the item weighting method from Kilic & Dogan (2019) <doi:10.21031/epod.516057>. To improve construct validity, this method re-computes scores by utilizing the item discrimination index in conjunction with a condition established upon person ability and item difficulty.

Builds survey analysis weights by declaring the whole weighting process as an ordered recipe of explicit adjustments, estimated in a single call. Steps cover within-cluster selection, subsampling for two-phase designs, nonresponse by weighting classes or response-propensity models (optionally machine-learning, with cross-fitting), calibration to known totals following Deville and Sarndal (1992) <doi:10.2307/2290268>, optionally model-assisted, non-probability samples by pseudo-weighting, mass imputation and doubly robust estimators, and range-restricted trimming. Rotating and pure panels add panel-selection probabilities, attrition, longitudinal weights, gross flows and composite estimation. Variances come from a recipe-aware bootstrap and jackknife that resample or delete primary sampling units and re-apply the entire cascade on each replicate, following Rao and Wu (1988) <doi:10.1080/01621459.1988.10478591>; panel replicates are coordinated across waves, so the sample overlap enters the variance of a net change as covariance, and two-phase variances split into first- and second-phase components (V = V1 + V2). A self-contained HTML report documents each step, and the weights bridge to the survey and srvyr packages. The methods, and the simulation evidence behind the variance estimators, are described in Ferreira (2026) <doi:10.1177/18747655261484262>.

An enhanced implementation of Whittaker-Henderson smoothing for the graduation of one-dimensional and two-dimensional actuarial tables used to quantify Life Insurance risks. WH is based on the methods described in Biessy (2025) <doi:10.48550/arXiv.2306.06932>. Among other features, it generalizes the original smoothing algorithm to maximum likelihood estimation, automatically selects the smoothing parameter(s) and extrapolates beyond the range of data.

The Wavelet Decomposition followed by Random Forest Regression (RF) models have been applied for time series forecasting. The maximum overlap discrete wavelet transform (MODWT) algorithm was chosen as it works for any length of the series. The series is first divided into training and testing sets. In each of the wavelet decomposed series, the supervised machine learning approach namely random forest was employed to train the model. This package also provides accuracy metrics in the form of Root Mean Square Error (RMSE) and Mean Absolute Prediction Error (MAPE). This package is based on the algorithm of Ding et al. (2021) <DOI: 10.1007/s11356-020-12298-3>.

Sort k-partite graphs with node order, layer order, and node grouping optimized with a heuristic to (nearly) minimize edge crossings. Useful for improving visualizations with alluvial plots by "untangling" the graphs.

This package provides a utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

This package provides data from the United Nation's World Population Prospects 2019.

An easy-to-use interface for interacting with WebDAV servers, including OwnCloud'. It simplifies the use of WebDAV methods such as COPY, MOVE, DELETE and others. With built-in authentication and request handling, it allows for easy management of files and directories over the WebDAV protocol.

The employment of the Wavelet decomposition technique proves to be highly advantageous in the modelling of noisy time series data. Wavelet decomposition technique using the "haar" algorithm has been incorporated to formulate a hybrid Wavelet KNN (K-Nearest Neighbour) model for time series forecasting, as proposed by Anjoy and Paul (2017) <DOI:10.1007/s00521-017-3289-9>.

This package provides functions to assist in the processing and exploration of data from environmental monitoring programs. The package name stands for "water quality" and reflects the original focus on time series data for physical and chemical properties of water, as well as the biota. Intended for programs that sample approximately monthly, quarterly or annually at discrete stations, a feature of many legacy data sets. Most of the functions should be useful for analysis of similar-frequency time series regardless of the subject matter.

This package provides unified syntax to write data from lazy dplyr tbl or dplyr sql query or a dataframe to a database table with modes such as create, append, insert, update, upsert, patch, delete, overwrite, overwrite_schema.

This package provides a powerful yet simple graphical tool available in the field of psychometrics is the Wright Map (also known as item maps or item-person maps), which presents the location of both respondents and items on the same scale. Wright Maps are commonly used to present the results of dichotomous or polytomous item response models. The WrightMap package provides functions to create these plots from item parameters and person estimates stored as R objects. Although the package can be used in conjunction with any software used to estimate the IRT model (e.g. TAM', mirt', eRm or IRToys in R', or Stata', Mplus', etc.), WrightMap features special integration with ConQuest to facilitate reading and plotting its output directly. The wrightMap function creates Wright Maps based on person estimates and item parameters produced by an item response analysis. The CQmodel function reads output files created using ConQuest software and creates a set of data frames for easy data manipulation, bundled in a CQmodel object. The wrightMap function can take a CQmodel object as input or it can be used to create Wright Maps directly from data frames of person and item parameters.

The outcome of various rehabilitation strategies for water distribution systems can be modeled with the Water Management Simulator (WaMaSim). Pipe breaks and the corresponding damage and rehabilitation costs are simulated. It is mainly intended to be used as educational tool for the Water Infrastructure Experimental and Computer Laboratory at ETH Zurich, Switzerland.

This package provides a single function to fit data of an input data frame into one of the selected Weibull functions (w2, w3 and it's truncated versions), calculating the scale, location and shape parameters accordingly. The resulting plots and files are saved into the folder parameter provided by the user. References: a) John C. Nash, Ravi Varadhan (2011). "Unifying Optimization Algorithms to Aid Software System Users: optimx for R" <doi:10.18637/jss.v043.i09>.

This package provides Apache and IIS log analytics for transaction performance, client populations and workload definitions.

Analyzes and models data subject to sampling biases. Provides functions to estimate the density and cumulative distribution functions from biased samples of continuous distributions. Includes the estimators proposed by Bhattacharyya et al. (1988) <doi:10.1080/03610928808829825> and Jones (1991) <doi:10.2307/2337020> for density, and by Cox (2005, ISBN:052184939X) and Bose and Dutta (2022) <doi:10.1007/s00184-021-00824-3> for distribution, with different bandwidth selectors. Also includes a real length-biased dataset on shrub width from Muttlak (1988) <https://www.proquest.com/openview/3dd74592e623cdbcfa6176e85bd3d390/1?cbl=18750&diss=y&pq-origsite=gscholar>.

Detects perceptions of warmth and competence in American English self-presentation language. Using trained elastic net regression models, this package provides a numerical representation of warmth and competence perceptions. Methods are described here:<https://github.com/bushraguenoun/warmthcompetence/tree/master/paper>.

This package provides functions are collected to analyse weather data for agriculture purposes including to read weather records in multiple formats, calculate extreme climate index. Demonstration data are included the SILO daily climate data (licensed under CC BY 4.0, <https://www.longpaddock.qld.gov.au/silo/>).

Retrieval the leaf area index (LAI) and soil moisture (SM) from microwave backscattering data using water cloud model (WCM) model . The WCM algorithm attributed to Pervot et al.(1993) <doi:10.1016/0034-4257(93)90053-Z>. The authors are grateful to SAC, ISRO, Ahmedabad for providing financial support to Dr. Prashant K Srivastava to conduct this research work.