This package implements the nonparametric causality-in-quantiles test (in mean or variance), returning a test object with an S3 plot() method. The current implementation uses one lag of each series (first-order Granger causality setup). Methodology is based on Balcilar, Gupta, and Pierdzioch (2016a) <doi:10.1016/j.resourpol.2016.04.004> and Balcilar et al. (2016) <doi:10.1007/s11079-016-9388-x>.

This package provides functions for manipulating nested data frames in a list-column using dplyr <https://dplyr.tidyverse.org/> syntax. Rather than unnesting, then manipulating a data frame, nplyr allows users to manipulate each nested data frame directly. nplyr is a wrapper for dplyr functions that provide tools for common data manipulation steps: filtering rows, selecting columns, summarising grouped data, among others.

To estimate ecological stochasticity in community assembly. Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. The new index, normalized stochasticity ratio (NST), is to estimate ecological stochasticity, i.e. relative importance of stochastic processes, in community assembly. With functions in this package, NST can be calculated based on different similarity metrics and/or different null model algorithms, as well as some previous indexes, e.g. previous Stochasticity Ratio (ST), Standard Effect Size (SES), modified Raup-Crick metrics (RC). Functions for permutational test and bootstrapping analysis are also included. Previous ST is published by Zhou et al (2014) <doi:10.1073/pnas.1324044111>. NST is modified from ST by considering two alternative situations and normalizing the index to range from 0 to 1 (Ning et al 2019) <doi:10.1073/pnas.1904623116>. A modified version, MST, is a special case of NST, used in some recent or upcoming publications, e.g. Liang et al (2020) <doi:10.1016/j.soilbio.2020.108023>. SES is calculated as described in Kraft et al (2011) <doi:10.1126/science.1208584>. RC is calculated as reported by Chase et al (2011) <doi:10.1890/ES10-00117.1> and Stegen et al (2013) <doi:10.1038/ismej.2013.93>. Version 3 added NST based on phylogenetic beta diversity, used by Ning et al (2020) <doi:10.1038/s41467-020-18560-z>.

This package provides a collection of colour palettes derived from photographs of nudis and sea slugs I have encountered in intertidal zones and shallow rocky reefs around Sydney, Australia. Palettes can be used in base R or with ggplot2'.

Given a network (e.g. a food web), estimates several network indices. These include: Ascendency network indices, Direct and indirect dependencies, Effective measures, Environ network indices, General network indices, Pathway analysis, Network uncertainty indices and constraint efficiencies and the trophic level and omnivory indices of food webs.

This package provides a toolkit for medical records data analysis. The naryn package implements an efficient data structure for storing medical records, and provides a set of functions for data extraction, manipulation and analysis.

This package implements spatial null models and coordinate-space transformations for statistical comparison of brain maps, following the framework described in Markello et al. (2022) <doi:10.1038/s41592-022-01625-w>. Provides variogram-matching surrogates (Burt et al. 2020), Moran spectral randomization (Wagner & Dray 2015), and spin-based permutation tests (Alexander-Bloch et al. 2018). Includes an R interface to the neuromaps annotation registry for browsing, downloading, and comparing brain map annotations from the Open Science Framework ('OSF'). Integrates with ciftiTools for coordinate-space transforms.

We connect the multi-class Neyman-Pearson classification (NP) problem to the cost-sensitive learning (CS) problem, and propose two algorithms (NPMC-CX and NPMC-ER) to solve the multi-class NP problem through cost-sensitive learning tools. Under certain conditions, the two algorithms are shown to satisfy multi-class NP properties. More details are available in the paper "Neyman-Pearson Multi-class Classification via Cost-sensitive Learning" (Ye Tian and Yang Feng, 2021).

R interface for the netstat command line utility used to retrieve and parse commonly used network statistics, including available and in-use transmission control protocol (TCP) ports. Primers offering technical background information on the netstat command line utility are available in the "Linux System Administrator's Manual" by Michael Kerrisk (2014) <https://man7.org/linux/man-pages/man8/netstat.8.html>, and on the Microsoft website (2017) <https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/netstat>.

Assist novice developers when preparing a single package or a set of integrated packages to submit to CRAN. Automate the following individual or batch processing: check local source packages; build local .tar.gz source files; install packages from local .tar.gz files; detect conflicts between function names in the environment.

Creation and selection of N-way Partial Least Squares (NPLS) models. Selection of the optimal number of components can be done using ncrossreg(). NPLS was originally described by Rasmus Bro, see <doi:10.1002/%28SICI%291099-128X%28199601%2910%3A1%3C47%3A%3AAID-CEM400%3E3.0.CO%3B2-C>.

This package provides functions for the normal Laplace distribution. Currently, it provides limited functionality. Density, distribution and quantile functions, random number generation, and moments are provided.

Essentials for PK/PD (pharmacokinetics/pharmacodynamics) such as area under the curve, (geometric) coefficient of variation, and other calculations that are not part of base R. This is not a noncompartmental analysis (NCA) package.

An extension of the Beta Kernel Process model designed to handle negative binomial responses for count data modeling, building upon Zhao, Qing and Xu (2025) <doi:10.48550/arXiv.2508.10447>.

This package provides tools for performing nowcasting using the Chain-Ladder method <https://en.wikipedia.org/wiki/Chain-ladder_method>. It supports both non-cumulative delay-based estimation and model-based completeness fitting (e.g., using logistic or Gompertz curves) to predict final counts from partially reported data.

This package contains a sample of the 2005 Grade 8 Mathematics data from the National Assessment of Educational Progress (NAEP). This data set is called the NAEP Primer.

To study network evolution models and different blockmodeling approaches. Various functions enable generating (temporal) networks with a selected blockmodel type, taking into account selected local network mechanisms. The development of this package is financially supported the Slovenian Research Agency (www.arrs.gov.si) within the research program P5<96>0168 and the research project J5-2557 (Comparison and evaluation of different approaches to blockmodeling dynamic networks by simulations with application to Slovenian co-authorship networks).

This package provides a near drop-in replacement for base::Sys.sleep() that allows more types of input to produce delays in the execution of code and can silence/prevent typical sources of error.

Estimates the relative transmission probabilities between cases in an infectious disease outbreak or cluster using naive Bayes. Included are various functions to use these probabilities to estimate transmission parameters such as the generation/serial interval and reproductive number as well as finding the contribution of covariates to the probabilities and visualizing results. The ideal use is for an infectious disease dataset with metadata on the majority of cases but more informative data such as contact tracing or pathogen whole genome sequencing on only a subset of cases. For a detailed description of the methods see Leavitt et al. (2020) <doi:10.1093/ije/dyaa031>.

This package provides visual citations containing the metadata of a scientific paper and a QR code. A visual citation is a banner containing title, authors, journal and year of a publication. This package can create such banners based on BibTeX and BibLaTeX references or call the reference metadata from Crossref'-API. The banners include a QR code pointing to the DOI'. The resulting HTML object or PNG image can be included in a presentation to point the audience to good resources for further reading. Styling is possible via predefined designs or via custom CSS'. This package is not intended as replacement for proper reference manager packages, but a tool to enrich scientific presentation slides and conference posters.

In this implementation of the Naive Bayes classifier following class conditional distributions are available: Bernoulli', Categorical', Gaussian', Poisson', Multinomial and non-parametric representation of the class conditional density estimated via Kernel Density Estimation. Implemented classifiers handle missing data and can take advantage of sparse data.

This package provides a collection of NASCAR race, driver, owner and manufacturer data across the three major NASCAR divisions: NASCAR Cup Series, NXS, and NASCAR Craftsman Truck Series. The curated data begins with the 1949 season and is updated weekly during the racing season. Explore race, season, or career performance for drivers, teams, and manufacturers throughout NASCAR's history. Data was sourced with permission from DriverAverages.com.

Tests the goodness-of-fit to the Normal distribution for the errors of an ARMA model.

This package provides customized forest plots for network meta-analysis incorporating direct, indirect, and NMA effects. Includes visualizations of evidence contributions through proportion bars based on the hat matrix and evidence flow decomposition.