Designed to create interactive and visually compelling network maps using R Shiny. It allows users to quickly analyze CSV files and visualize complex relationships, structures, and connections within data by leveraging powerful network analysis libraries and dynamic web interfaces.

NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D biological image data, especially traced neurons. Reads and writes 3D images in NRRD and Amira AmiraMesh formats and reads surfaces in Amira hxsurf format. Traced neurons can be imported from and written to SWC and Amira LineSet and SkeletonGraph formats. These data can then be visualised in 3D via rgl', manipulated including applying calculated registrations, e.g. using the CMTK registration suite, and analysed. There is also a simple representation for neurons that have been subjected to 3D skeletonisation but not formally traced; this allows morphological comparison between neurons including searches and clustering (via the nat.nblast extension package).

Wald Test for nonlinear restrictions on model parameters and confidence intervals for nonlinear functions of parameters using delta-method. Applicable after ANY model, provided parameters estimates and their covariance matrix are available.

This package provides functions and datasets to support the book by Galecki and Burzykowski (2013), Linear Mixed-Effects Models: A Step-by-Step Approach', Springer. Includes functions for power calculations, log-likelihood contributions, and data simulation for linear mixed-effects models.

This package provides standardized access to a range of re-scaling methods for numerical vectors and time-series features calculated within the theft ecosystem.

Includes five particle filtering algorithms for use with state space models in the nimble system: Auxiliary', Bootstrap', Ensemble Kalman filter', Iterated Filtering 2', and Liu-West', as described in Michaud et al. (2021), <doi:10.18637/jss.v100.i03>. A full User Manual is available at <https://r-nimble.org>.

Estimate the correlation between two NIfTI images across random parcellations of the images (Fortea et al., under review). This approach overcomes the problems of both voxel-based correlations (neighbor voxels may be spatially dependent) and atlas-based correlations (the correlation may depend on the atlas used).

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

This package creates quasi-proportional Venn diagrams with an arbitrary number of sets. It is related to the old nVennR package, but the algorithm and use have been reworked.

This package provides a reproducible workflow for binning and visualizing NMR (nuclear magnetic resonance) spectra from environmental samples. The nmrrr package is intended for post-processing of NMR data, including importing, merging and, cleaning data from multiple files, visualizing NMR spectra, performing binning/integrations for compound classes, and relative abundance calculations. This package can be easily inserted into existing analysis workflows by users to help with analyzing and interpreting NMR data.

This package provides a nested menu widget for usage in Shiny applications. This is useful for hierarchical choices (e.g. continent, country, city).

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>.

This package provides several novel exact hypothesis tests with minimal assumptions on the errors. The tests are exact, meaning that their p-values are correct for the given sample sizes (the p-values are not derived from asymptotic analysis). The test for stochastic inequality is for ordinal comparisons based on two independent samples and requires no assumptions on the errors. The other tests include tests for the mean and variance of a single sample and comparing means in independent samples. All these tests only require that the data has known bounds (such as percentages that lie in [0,100]. These bounds are part of the input.

Calculation and presentation of decision-invariant bias adjustment thresholds and intervals for Network Meta-Analysis, as described by Phillippo et al. (2018) <doi:10.1111/rssa.12341>. These describe the smallest changes to the data that would result in a change of decision.

Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente, et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN: 9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others (2011) <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among others.

This package provides a permutation-based hypothesis test for statistical comparison of two networks based on the invariance measures of the R package NetworkComparisonTest by van Borkulo et al. (2022), <doi:10.1037/met0000476>: network structure invariance, global strength invariance, edge invariance, and various centrality measures. Edgelists from dependent or independent samples are used as input. These edgelists are generated from concept maps and summed into two comparable group networks. The networks can be directed or undirected.

The Bayesian hierarchical model named antigen-T cell interaction estimation is to estimate the history of the immune pressure on the evolution of the tumor clones.The model is based on the estimation result from Andrew Roth (2014) <doi:10.1038/nmeth.2883>.

This package provides functions to access NASA's Earth Imagery and Assets API and the Earth Observatory Natural Event Tracker (EONET) webservice.

This package provides a method for obtaining nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers or splines. Additionally, a parametric model (allometric model) can be estimated.

Conduct inference on the sample average treatment effect for a matched (observational) dataset with a continuous treatment. Equipped with calipered non-bipartite matching, bias-corrected sample average treatment effect estimation, and covariate-adjusted variance estimation. Matching, estimation, and inference methods are described in Frazier, Heng and Zhou (2024) <doi:10.48550/arXiv.2409.11701>.

This package implements the navigated weighting (NAWT) proposed by Katsumata (2020) <arXiv:2005.10998>, which improves the inverse probability weighting by utilizing estimating equations suitable for a specific pre-specified parameter of interest (e.g., the average treatment effects or the average treatment effects on the treated) in propensity score estimation. It includes the covariate balancing propensity score proposed by Imai and Ratkovic (2014) <doi:10.1111/rssb.12027>, which uses covariate balancing conditions in propensity score estimation. The point estimate of the parameter of interest as well as coefficients for propensity score estimation and their uncertainty are produced using the M-estimation. The same functions can be used to estimate average outcomes in missing outcome cases.

This package provides a collection of datasets related to neutrosophic sets for statistical modeling and analysis.

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/>.

Implementation of the NetCutter algorithm described in Müller and Mancuso (2008) <doi:10.1371/journal.pone.0003178>. The package identifies co-occurring terms in a list of containers. For example, it may be used to detect genes that co-occur across genomes.