The National Ecological Observatory Network (NEON) provides access to its numerous data products through its REST API, <https://data.neonscience.org/data-api/>. This package provides a high-level user interface for downloading and storing NEON data products. Unlike neonUtilities', this package will avoid repeated downloading, provides persistent storage, and improves performance. neonstore can also construct a local duckdb database of stacked tables, making it possible to work with tables that are far to big to fit into memory.

This package provides functions to use the NamePrism API <https://www.name-prism.com/api> or NamSor API v2 <https://namsor.app/> for classifying names based on gender, 6 U.S. ethnicities, or 39 leaf nationalities. Updated to work with current API endpoints.

Estimates micro effects on macro structures (MEMS) and average micro mediated effects (AMME). URL: <https://github.com/sduxbury/netmediate>. BugReports: <https://github.com/sduxbury/netmediate/issues>. Robins, Garry, Phillipa Pattison, and Jodie Woolcock (2005) <doi:10.1086/427322>. Snijders, Tom A. B., and Christian E. G. Steglich (2015) <doi:10.1177/0049124113494573>. Imai, Kosuke, Luke Keele, and Dustin Tingley (2010) <doi:10.1037/a0020761>. Duxbury, Scott (2023) <doi:10.1177/00811750231209040>. Duxbury, Scott (2024) <doi:10.1177/00811750231220950>.

Format numbers and plots for publication; includes the removal of leading zeros, standardization of number of digits, addition of affixes, and a p-value formatter. These tools combine the functionality of several base functions such as paste()', format()', and sprintf() into specific use case functions that are named in a way that is consistent with usage, making their names easy to remember and easy to deploy.

Implementation of models for the controlled introduction of errors in classification datasets. This package contains the noise models described in Saez (2022) <doi:10.3390/math10203736> that allow corrupting class labels, attributes and both simultaneously.

Geospatial data for creating maps of New South Wales (NSW), Australia, and some helpers to work with common problems like normalising postcodes. Registers its data with cartographer'.

This package provides a Software Development Kit for working with Nixtla''s TimeGPT', a foundation model for time series forecasting. API is an acronym for application programming interface'; this package allows users to interact with TimeGPT via the API'. You can set and validate API keys and generate forecasts via API calls. It is compatible with tsibble and base R. For more details visit <https://www.nixtla.io/docs>.

Segmentation of short text sequences - like hashtags - into the separated words sequence, done with the use of dictionary, which may be built on custom corpus of texts. Unigram dictionary is used to find most probable sequence, and n-grams approach is used to determine possible segmentation given the text corpus.

Predicting the structure of a graph including new nodes and edges using a time series of graphs. Flux balance analysis, a linear and integer programming technique used in biochemistry is used with time series prediction methods to predict the graph structure at a future time point Kandanaarachchi (2025) <doi:10.48550/arXiv.2507.05806>.

This package provides a collection of utilities referred to Exponential Power distribution, also known as General Error Distribution (see Mineo, A.M. and Ruggieri, M. (2005), A software Tool for the Exponential Power Distribution: The normalp package. In Journal of Statistical Software, Vol. 12, Issue 4).

This package provides tools for modelling, ML estimation, validation analysis and simulation of non homogeneous Poisson processes in time.

Designed to automate the calculation of Emergency Medical Service (EMS) quality metrics, nemsqar implements measures defined by the National EMS Quality Alliance (NEMSQA). By providing reliable, evidence-based quality assessments, the package supports EMS agencies, healthcare providers, and researchers in evaluating and improving patient outcomes. Users can find details on all approved NEMSQA measures at <https://www.nemsqa.org/measures>. Full technical specifications, including documentation and pseudocode used to develop nemsqar', are available on the NEMSQA website after creating a user profile at <https://www.nemsqa.org>.

Acquires and synthesizes soil carbon fluxes at sites located in the National Ecological Observatory Network (NEON). Provides flux estimates and associated uncertainty as well as key environmental measurements (soil water, temperature, CO2 concentration) that are used to compute soil fluxes.

This package provides a SQLite-backed cell-level cache that can be used as a drop-in backend by the nordstat family of packages ('rKolada', rTrafa', and pixieweb'). Designed for multi-user web applications where minimal fetch latency and asynchronous writes are required. Individual statistical values ("cells") are stored in a gatekeeper schema with a sidecar table for arbitrary metadata dimensions, enabling deduplication across overlapping queries.

Nested Partially Balanced Bipartite Block (NPBBB) designs involve two levels of blocking: (i) The block design (ignoring sub-block classification) serves as a partially balanced bipartite block (PBBB) design, and (ii) The sub-block design (ignoring block classification) also serves as a PBBB design. More details on constructions of the PBBB designs and their characterization properties are available in Vinayaka et al.(2023) <doi:10.1080/03610926.2023.2251623>. This package calculates A-efficiency values for both block and sub-block structures, along with all parameters of a given NPBBB design.

This package provides a suite of functions to work with data from the National Institutes of Health Brain Development Cohorts Data Hub. The package provides tools to create, clean, process, and filter datasets and associated metadata. These utilities are intended to simplify reproducible data-preparation for future research.

Efficient tools for preparation, checking and post-processing of data in PK/PD (pharmacokinetics/pharmacodynamics) modeling, with focus on use of Nonmem, including consistency, traceability, and Nonmem compatibility of Data. Rigorously checks final Nonmem datasets. Implemented in data.table', but easily integrated with base and tidyverse'.

The Negative Binomial regression with mean and shape modeling and mean and variance modeling and Beta Binomial regression with mean and dispersion modeling.

Calculates network measures commonly used in Network Medicine. Measures such as the Largest Connected Component, the Relative Largest Connected Component, Proximity and Separation are calculated along with their statistical significance. Significance can be computed both using a degree-preserving randomization and non-degree preserving.

Providing a common set of simplified web scraping tools for working with the NHS Data Dictionary <https://datadictionary.nhs.uk/data_elements_overview.html>. The intended usage is to access the data elements section of the NHS Data Dictionary to access key lookups. The benefits of having it in this package are that the lookups are the live lookups on the website and will not need to be maintained. This package was commissioned by the NHS-R community <https://nhsrcommunity.com/> to provide this consistency of lookups. The OpenSafely lookups have now been added <https://www.opencodelists.org/docs/>.

Designed to replace the tables which were in the back of the first two editions of Hollander and Wolfe - Nonparametric Statistical Methods. Exact procedures are performed when computationally possible. Monte Carlo and Asymptotic procedures are performed otherwise. For those procedures included in the base packages, our code simply provides a wrapper to standardize the output with the other procedures in the package.

Simulation, estimation, prediction procedure, and model identification methods for nonlinear time series analysis, including threshold autoregressive models, Markov-switching models, convolutional functional autoregressive models, nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. More examples and details about this package can be found in the book "Nonlinear Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: 978-1-119-26407-1).

This package provides functions to fit linear mixed models based on convolutions of the generalized Laplace (GL) distribution. The GL mixed-effects model includes four special cases with normal random effects and normal errors (NN), normal random effects and Laplace errors (NL), Laplace random effects and normal errors (LN), and Laplace random effects and Laplace errors (LL). The methods are described in Geraci and Farcomeni (2020, Statistical Methods in Medical Research) <doi:10.1177/0962280220903763>.

This package provides efficient methods to compute co-occurrence matrices, pointwise mutual information (PMI) and singular value decomposition (SVD). In the biomedical and clinical settings, one challenge is the huge size of databases, e.g. when analyzing data of millions of patients over tens of years. To address this, this package provides functions to efficiently compute monthly co-occurrence matrices, which is the computational bottleneck of the analysis, by using the RcppAlgos package and sparse matrices. Furthermore, the functions can be called on SQL databases, enabling the computation of co-occurrence matrices of tens of gigabytes of data, representing millions of patients over tens of years. Partly based on Hong C. (2021) <doi:10.1038/s41746-021-00519-z>.