An interface to WordNet using the Jawbone Java API to WordNet. WordNet (<https://wordnet.princeton.edu/>) is a large lexical database of English. Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic and lexical relations. Please note that WordNet(R) is a registered tradename. Princeton University makes WordNet available to research and commercial users free of charge provided the terms of their license (<https://wordnet.princeton.edu/license-and-commercial-use>) are followed, and proper reference is made to the project using an appropriate citation (<https://wordnet.princeton.edu/citing-wordnet>). The WordNet database files need to be made available separately, either via package wordnetDicts from <https://datacube.wu.ac.at>, installing system packages where available, or direct download from <https://wordnetcode.princeton.edu/3.0/WNdb-3.0.tar.gz>.

High-level tools to attach gridded weather data from the NASA POWER Project to event-based datasets. The package plans efficient spatio-temporal API calls via the nasapower R package, caches downloaded segments locally, and joins weather variables back to the input table using exact or rolling joins. This package is not affiliated with or endorsed by NASA.

Use various regression models for the analysis of win loss endpoints adjusting for non-binary and multivariate covariates.

Explore data in the wpp2019 (or 2017, 2015, ...) package using a shiny interface.

This package provides a toolkit to set up an R data package in a consistent structure. Automates tasks like tidy data export, data dictionary documentation, README and website creation, and citation management.

Urban water and sanitation survey dataset collected by Water and Sanitation for the Urban Poor (WSUP) with technical support from Valid International. These citywide surveys have been collecting data allowing water and sanitation service levels across the entire city to be characterised, while also allowing more detailed data to be collected in areas of the city of particular interest. These surveys are intended to generate useful information for others working in the water and sanitation sector. Current release version includes datasets collected from a survey conducted in Dhaka, Bangladesh in March 2017. This survey in Dhaka is one of a series of surveys to be conducted by WSUP in various cities in which they operate including Accra, Ghana; Nakuru, Kenya; Antananarivo, Madagascar; Maputo, Mozambique; and, Lusaka, Zambia. This package will be updated once the surveys in other cities are completed and datasets have been made available.

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

This package provides functions for subject/instance weighted support vector machines (SVM). It uses a modified version of libsvm and is compatible with package e1071'. It also allows user defined kernel matrix.

Time series outlier detection with non parametric test. This is a new outlier detection methodology (washer): efficient for time saving elaboration and implementation procedures, adaptable for general assumptions and for needing very short time series, reliable and effective as involving robust non parametric test. You can find two approaches: single time series (a vector) and grouped time series (a data frame). For other informations: Andrea Venturini (2011) Statistica - Universita di Bologna, Vol.71, pp.329-344. For an informal explanation look at R-bloggers on web.

The wavelet and ANN technique have been combined to reduce the effect of data noise. This wavelet-ANN conjunction model is able to forecast time series data with better accuracy than the traditional time series model. This package fits hybrid Wavelet ANN model for time series forecasting using algorithm by Anjoy and Paul (2017) <DOI: 10.1007/s00521-017-3289-9>.

The word puzzle game requires you to find out the letters in a word within a limited number of guesses. In each round, if your guess hit any letters in the word, they reveal themselves. If all letters are revealed before your guesses run out, you win this game; otherwise you fail. You may run multiple games to guess different words.

Evaluation of prediction performance of smaller regions of spectra for Chemometrics. Segmentation of spectra, evolving dimensions regions and sliding windows as selection methods. Election of the best model among those computed based on error metrics. Chen et al.(2017) <doi:10.1007/s00216-017-0218-9>.

Application to estimate statistical values using properties provided by a group of individuals to describe concepts using shiny'. It estimates the underlying distribution to generate new descriptive words Canessa et al. (2023) <doi:10.3758/s13428-022-01811-w>, applies a new clustering model, and uses simulations to estimate the probability that two persons describe the same words based on their descriptions Canessa et al. (2022) <doi:10.3758/s13428-022-02030-z>.

Imports WhatsApp chat logs and parses them into a usable dataframe object. The parser works on chats exported from Android or iOS phones and on Linux, macOS and Windows. The parser has multiple options for extracting smileys and emojis from the messages, extracting URLs and domains from the messages, extracting names and types of sent media files from the messages, extracting timestamps from messages, extracting and anonymizing author names from messages. Can be used to create anonymized versions of data.

This package provides API access to the Walmart Open API <https://developer.walmartlabs.com/>, that contains data about stores, Value of the day and products which includes names, sale prices, shipping rates and taxonomies.

Calculate the win statistics (win ratio, net benefit and win odds) for prioritized multiple endpoints, plot the win statistics and win proportions over study time if at least one time-to-event endpoint is analyzed, and simulate datasets with dependent endpoints. The package can handle any type of outcomes (continuous, ordinal, binary, time-to-event) and allow users to perform stratified analysis, inverse probability of censoring weighting (IPCW) and inverse probability of treatment weighting (IPTW) analysis.

Logging of scripts suitable for clinical trials using Quarto to create nice human readable logs. whirl enables execution of scripts in batch, while simultaneously creating logs for the execution of each script, and providing an overview summary log of the entire batch execution.

Spatial data are generally auto-correlated, meaning that if two units selected are close to each other, then it is likely that they share the same properties. For this reason, when sampling in the population it is often needed that the sample is well spread over space. A new method to draw a sample from a population with spatial coordinates is proposed. This method is called wave (Weakly Associated Vectors) sampling. It uses the less correlated vector to a spatial weights matrix to update the inclusion probabilities vector into a sample. For more details see Raphaël Jauslin and Yves Tillé (2019) <doi:10.1007/s13253-020-00407-1>.

Select data analysis plots, under a standardized calling interface implemented on top of ggplot2 and plotly'. Plots of interest include: ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.

This package provides inference for the Wilcoxon-Mann-Whitney test under the null hypothesis H0: AUC = 0.5 for continuous, discrete or mixed random variables. Traditional implementations test H0: F = G, which is inappropriately broad and leads to erroneous inferences. Methods are described in M. Grendar (2025) "Wilcoxon-Mann-Whitney Test of No Group Discrimination" <doi:10.48550/arXiv.2511.20308>.

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>.

Four filters have been chosen namely haar', c6', la8', and bl14 (Kindly refer to wavelets in CRAN repository for more supported filters). Levels of decomposition are 2, 3, 4, etc. up to maximum decomposition level which is ceiling value of logarithm of length of the series base 2. For each combination two models are run separately. Results are stored in input'. First five metrics are expected to be minimum and last three metrics are expected to be maximum for a model to be considered good. Firstly, every metric value (among first five) is searched in every columns and minimum values are denoted as MIN and other values are denoted as NA'. Secondly, every metric (among last three) is searched in every columns and maximum values are denoted as MAX and other values are denoted as NA'. output contains the similar number of rows (which is 8) and columns (which is number filter-level combinations) as of input'. Values in output are corresponding NA', MIN or MAX'. Finally, the column containing minimum number of NA values is denoted as the best ('FL'). In special case, if two columns having equal NA', it has been checked among these two columns which one is having least NA in first five rows and has been inferred as the best. FL_metrics_values are the corresponding metrics values. WARIGAANbest is the data frame (dimension: 1*8) containing different metrics of the best filter-level combination. More details can be found in Garai and others (2023) <doi:10.13140/RG.2.2.11977.42087>.

Streamlines the process of transitioning between data formats commonly used in survival analysis. Functions convert longitudinal data between formats used as input for survival models as well as support overall preparation. Users are able to focus on model building rather than data wrangling.

Additional options for making graphics in the context of analyzing high-throughput data are available here. This includes automatic segmenting of the current device (eg window) to accommodate multiple new plots, automatic checking for optimal location of legends in plots, small histograms to insert as legends, histograms re-transforming axis labels to linear when plotting log2-transformed data, a violin-plot <doi:10.1080/00031305.1998.10480559> function for a wide variety of input-formats, principal components analysis (PCA) <doi:10.1080/14786440109462720> with bag-plots <doi:10.1080/00031305.1999.10474494> to highlight and compare the center areas for groups of samples, generic MA-plots (differential- versus average-value plots) <doi:10.1093/nar/30.4.e15>, staggered count plots and generation of mouse-over interactive html pages.