Estimates high-dimensional multivariate normal copula regression models with the weighted composite likelihood estimating equations in Nikoloulopoulos (2022) <arXiv:2203.04619>. It provides autoregressive moving average correlation structures and binary, ordinal, Poisson, and negative binomial regressions.

An adaptation for estuaries (tidal waters) of weighted regression on time, discharge, and season to evaluate trends in water quality time series. Please see Beck and Hagy (2015) <doi:10.1007/s10666-015-9452-8> for details.

This package infers cell type-specific expression based on co-expression similarity with known cell type marker genes. Can make accurate predictions using publicly available expression data, even when a cell type has not been isolated before.

By leveraging statistical properties (log-rank test for survival) of patient cohorts defined by binary thresholds, poor-prognosis patients are identified by the sigsquared package via optimization over a cost function reducing type I and II error.

This package supports the application of diverse quality metrics to AffyBatch instances, summarizing these metrics via PCA, and then performing parametric outlier detection on the PCs to identify aberrant arrays with a fixed Type I error rate.

This is yet another command-line argument parser which wraps the powerful Perl module Getopt::Long and with some adaptation for easier use in R. It also provides a simple way for variable interpolation in R.

This package provides a collection of functions to support matrix calculations for probability, econometric and numerical analysis. There are additional functions that are comparable to APL functions which are useful for actuarial models such as pension mathematics.

This package provides wrapper types and traits for secret management which help ensure they aren't accidentally copied, logged, or otherwise exposed (as much as possible), and also ensure secrets are securely wiped from memory when dropped.

This package provides wrapper types and traits for secret management which help ensure they aren't accidentally copied, logged, or otherwise exposed (as much as possible), and also ensure secrets are securely wiped from memory when dropped.

Timecop provides "time travel" and "time freezing" capabilities, making it easier to test time-dependent code. It provides a unified method to mock Time.now, Date.today, and DateTime.now in a single call.

This package provides a backend for the selecting functions of the tidyverse. It makes it easy to implement select-like functions in your own packages in a way that is consistent with other tidyverse interfaces for selection.

Includes data analysis and meta-analysis functions (e.g., to calculate effect sizes and 95% Confidence Intervals (CI) on Standardised Effect Sizes (d) for AB/BA cross-over repeated-measures experimental designs), data presentation functions (e.g., density curve overlaid on histogram),and the data sets analyzed in different research papers in software engineering (e.g., related to software defect prediction or multi- site experiment concerning the extent to which structured abstracts were clearer and more complete than conventional abstracts) to streamline reproducible research in software engineering.

An interactive document on the topic of one-way and two-way analysis of variance using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://tinyurl.com/ANOVAStatsTool>.

This package provides functions for estimating and reporting multi-year averages and corresponding confidence intervals and distributions. A potential use case is reporting the chemical and ecological status of surface waters according to the European Water Framework Directive.

Event dataset repository including both real-life and artificial event logs. They can be used in combination with functionalities provided by the bupaR packages. Janssenswillen et al. (2020) <http://ceur-ws.org/Vol-2703/paperTD7.pdf>.

Transformations that allow obtaining a flat table from reports in text or Excel format that contain data in the form of pivot tables. They can be defined for a single report and applied to a set of reports.

Quickly and easily perform exploratory data analysis by uploading your data as a csv file. Start generating insights using ggplot2 plots and table1 tables with descriptive stats, all using an easy-to-use point and click Shiny interface.

This package provides a generic function and a set of methods to calculate highest density intervals for a variety of classes of objects which can specify a probability density distribution, including MCMC output, fitted density objects, and functions.

Companion package to the book "industRial data science", J.Ramalho (2021) <https://j-ramalho.github.io/industRial/>. Provides data sets and functions to complete the case studies and contains the book original Rmd files and tutorials.

Package shiny provides interactive web applications in R. Package loon is an interactive toolkit engaged in open-ended, creative and unscripted data exploration. The loon.shiny package can take loon widgets and display a selfsame shiny app.

Programmatic interface to the Oak Ridge National Laboratories MODIS Land Products Subsets web services (<https://modis.ornl.gov/data/modis_webservice.html>). Allows for easy downloads of MODIS time series directly to your R workspace or your computer.

This package implements a general interface for model-based estimations for a wide variety of models, used in the computation of marginal means, contrast analysis and predictions. For a list of supported models, see insight::supported_models()'.

Network Pre-Processing and normalization. Methods for normalizing graphs, including Chua normalization, Laplacian normalization, Binary magnification, min-max normalization and others. Methods to sparsify adjacency matrices. Methods for graph pre-processing and for filtering edges of the graph.

Datasets of driving offences and fines in New Zealand between 2009 and 2017. Originally published by the New Zealand Police at <http://www.police.govt.nz/about-us/publication/road-policing-driver-offence-data-january-2009-december-2017>.