Enables users to retrieve data, meta-data, and codebooks from <https://nettskjema.no/>. The data from the API is richer than from the online data portal. This package is not developed by the University of Oslo IT. Mowinckel (2021) <doi:10.5281/zenodo.4745481>.

This package contains data, code, and figures from Hill et al. 2018a (Journal of Experimental Marine Biology and Ecology; <DOI: 10.1016/j.jembe.2018.07.006>) and Hill et al. 2018b (Data In Brief <DOI: 10.1016/j.dib.2018.09.133>). Datasets document plant allometry, stem heights, nutrient and stable isotope content, and sediment denitrification enzyme assays. The data and analysis offer an examination of nitrogen uptake and allocation in two salt marsh plant species.

Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions modeling oriented towards flow-cytometry data preprocessing applications. Method is detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) <doi: 10.1214/18-AOAS1209>.

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.

Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the rxode2 package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>).

This permutation based hypothesis test, suited for several types of data supported by the estimateNetwork function of the bootnet package (Epskamp & Fried, 2018), assesses the difference between two networks based on several invariance measures (network structure invariance, global strength invariance, edge invariance, several centrality measures, etc.). Network structures are estimated with l1-regularization. The Network Comparison Test is suited for comparison of independent (e.g., two different groups) and dependent samples (e.g., one group that is measured twice). See van Borkulo et al. (2021), available from <doi:10.1037/met0000476>.

R binding over the nirs4all-datasets C ABI ('n4ds_*'): resolve a dataset id from the distributable catalog index into a version-pinned download contract, fetch the canonical Parquet ('Dataverse / Zenodo / figshare') with SHA-256 verification into a local cache, and re-verify a cached directory offline. JSON crosses the stable C ABI'; analysis of the data is left to the host.

An R-package for calculating sample size of a survival trial with or without cure fractions.

This package provides nonparametric CUSUM tests for detecting changes in possibly serially dependent univariate or low-dimensional multivariate observations. Retrospective tests sensitive to changes in the expectation, the variance, the covariance, the autocovariance, the distribution function, Spearman's rho, Kendall's tau, Gini's mean difference, and the copula are provided, as well as a test for detecting changes in the distribution of independent block maxima (with environmental studies in mind). The package also contains a test sensitive to changes in the autocopula and a combined test of stationarity sensitive to changes in the distribution function and the autocopula. The latest additions are an open-end sequential test based on the retrospective CUSUM statistic that can be used for monitoring changes in the mean of possibly serially dependent univariate observations, as well as closed-end and open-end sequential tests based on empirical distribution functions that can be used for monitoring changes in the contemporary distribution of possibly serially dependent univariate or low-dimensional multivariate observations.

This package provides the Arctic Ice Studio's Nord and Group of Seven inspired colour palettes for use with ggplot2 via custom functions.

Computes and plots the boundary between night and day.

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/>.

This package provides functions for adaptive parallel tempering (APT) with NIMBLE models. Adapted from Lacki & Miasojedow (2016) <DOI:10.1007/s11222-015-9579-0> and Miasojedow, Moulines and Vihola (2013) <DOI:10.1080/10618600.2013.778779>.

This package provides functions to query databases and notes in Notion', using the official REST API. To learn more about the functionality of the Notion API, see <https://developers.notion.com/>.

This package provides a functional programming based implementation of the super learner algorithm with an emphasis on supporting the use of formulas to specify learners. This approach offers several improvements compared to past implementations including the ability to easily use random-effects specified in formulas (like y ~ (age | strata) + ...) and construction of new learners is as simple as writing and passing a new function. The super learner algorithm was originally described in van der Laan et al. (2007) <https://biostats.bepress.com/ucbbiostat/paper222/>.

Conduct a noncompartmental analysis with industrial strength. Some features are 1) Use of CDISC SDTM terms 2) Automatic or manual slope selection 3) Supporting both linear-up linear-down and linear-up log-down method 4) Interval(partial) AUCs with linear or log interpolation method 5) Installation/Operational Qualification (IQ/OQ) reports in pdf. After installation, qualify the package in your own environment: run IQNCA() for Installation Qualification and OQNCA() for Operational Qualification. Run writeMD5NCA() once after installation so the IQ file-integrity check passes. To approve a report, sign it digitally in Adobe Acrobat Reader (generate with sigField=TRUE, or run addSigFieldNCA(), to add click-to-sign fields), instead of printing and scanning; or use signPDFNCA()/verifyPDFNCA() for a scriptable signature. * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107).

This package provides gradient-based MCMC sampling algorithms for use with the MCMC engine provided by the nimble package. This includes two versions of Hamiltonian Monte Carlo (HMC) No-U-Turn (NUTS) sampling, and (under development) Langevin samplers. The `NUTS_classic` sampler implements the original HMC-NUTS algorithm as described in Hoffman and Gelman (2014) <doi:10.48550/arXiv.1111.4246>. The `NUTS` sampler is a modern version of HMC-NUTS sampling matching the HMC sampler available in version 2.32.2 of Stan (Stan Development Team, 2023). In addition, convenience functions are provided for generating and modifying MCMC configuration objects which employ HMC sampling. Functionality of the nimbleHMC package is described further in Turek, et al (2024) <doi: 10.21105/joss.06745>.

Computes interdaily stability (IS), intradaily variability (IV) & the relative amplitude (RA) from actigraphy data as described in Blume et al. (2016) <doi: 10.1016/j.mex.2016.05.006> and van Someren et al. (1999) <doi: 10.3109/07420529908998724>. Additionally, it also computes L5 (i.e. the 5 hours with lowest average actigraphy amplitude) and M10 (the 10 hours with highest average amplitude) as well as the respective start times. The flex versions will also compute the L-value for a user-defined number of minutes. IS describes the strength of coupling of a rhythm to supposedly stable zeitgebers. It varies between 0 (Gaussian Noise) and 1 for perfect IS. IV describes the fragmentation of a rhythm, i.e. the frequency and extent of transitions between rest and activity. It is near 0 for a perfect sine wave, about 2 for Gaussian noise and may be even higher when a definite ultradian period of about 2 hrs is present. RA is the relative amplitude of a rhythm. Note that to obtain reliable results, actigraphy data should cover a reasonable number of days.

Makes NCBI taxonomic data locally available and searchable as an R object.

Generates functional Magnetic Resonance Imaging (fMRI) time series or 4D data. Some high-level functions are created for fast data generation with only a few arguments and a diversity of functions to define activation and noise. For more advanced users it is possible to use the low-level functions and manipulate the arguments. See Welvaert et al. (2011) <doi:10.18637/jss.v044.i10>.

This package implements various simple function utilities and flexible pipelines to generate circular images for visualizing complex genomic and network data analysis features.

This package provides methods for neutrosophic analysis of variance (NANOVA) and neutrosophic analysis of covariance (NANCOVA) for interval-valued data arising from incomplete block design experiments. The package supports balanced incomplete block designs (BIBDs), partially balanced incomplete block designs (PBIBDs), and lattice designs. Functions are included for treatment comparisons, least significant difference (LSD) tests, and interval-based statistical inference under neutrosophic environments.

Palettes generated from NBA jersey colorways.

Search, preview, and download datasets from the National Health and Nutrition Examination Survey (NHANES) across survey cycles. The package provides functions to identify relevant datasets by keyword, inspect available .XPT files before downloading, and organize retrieved data locally. Data are retrieved from the NHANES web services available at <https://wwwn.cdc.gov/nchs/nhanes/> .