This package provides Scilab n1qn1'. This takes more memory than traditional L-BFGS. The n1qn1 routine is useful since it allows prespecification of a Hessian. If the Hessian is near enough the truth in optimization it can speed up the optimization problem. The algorithm is described in the Scilab optimization documentation located at <https://www.scilab.org/sites/default/files/optimization_in_scilab.pdf>. This version uses manually modified code from f2c to make this a C only binary.

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).

An adaptation of Non-dominated Sorting Genetic Algorithm III for multi objective feature selection tasks. Non-dominated Sorting Genetic Algorithm III is a genetic algorithm that solves multiple optimization problems simultaneously by applying a non-dominated sorting technique. It uses a reference points based selection operator to explore solution space and preserve diversity. See the original paper by K. Deb and H. Jain (2014) <DOI:10.1109/TEVC.2013.2281534> for a detailed description.

This package provides a collection of network analytic (convenience) functions which are missing in other standard packages. This includes triad census with attributes <doi:10.1016/j.socnet.2019.04.003>, core-periphery models <doi:10.1016/S0378-8733(99)00019-2>, and several graph generators. Most functions are build upon igraph'.

Perform an exploration and a preliminary analysis on the dose- response relationship of nanomaterial toxicity. Several functions are provided for data exploration, including functions for creating a subset of dataset, frequency tables and plots. Inference for order restricted dose- response data is performed by testing the significance of monotonic dose-response relationship, using Williams, Marcus, M, Modified M and Likelihood ratio tests. Several methods of multiplicity adjustment are also provided. Description of the methods can be found in <https://github.com/rahmasarina/dose-response-analysis/blob/main/Methodology.pdf>.

The purpose of this library is to to call different optimization solvers (such as Gonzalez Rodriguez et al. (2022) <doi:10.1007/s10898-022-01229-w>, Tawarmalani and Sahinidis (2005) <doi:10.1007/s10107-005-0581-8>, and Byrd et al. (2006) <doi:10.1007/0-387-30065-1_4>) to solve problems given by a standard nl file.

Implementation of a probabilistic method to calculate nicheROVER (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions. It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region. The article by Swanson et al. (2015) <doi:10.1890/14-0235.1> provides a detailed description of the methodology. See the package vignette for a worked example using fish stable isotope data.

Next-Generation Clustered Heat Maps (NG-CHMs) allow for dynamic exploration of heat map data in a web browser. NGCHM allows users to create both stand-alone HTML files containing a Next-Generation Clustered Heat Map, and .ngchm files to view in the NG-CHM viewer. See Ryan MC, Stucky M, et al (2020) <doi:10.12688/f1000research.20590.2> for more details.

This package performs nonparametric estimation in mixture cure models, and significance tests for the cure probability. For details, see López-Cheda et al. (2017a) <doi:10.1016/j.csda.2016.08.002> and López-Cheda et al. (2017b) <doi:10.1007/s11749-016-0515-1>.

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

Derives the most frequent hierarchies along with their probability of occurrence. One can also define complex hierarchy criteria and calculate their probability. Methodology based on Papakonstantinou et al. (2021) <DOI:10.21203/rs.3.rs-858140/v1>.

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.

This package contains a collection of functions for performing different kinds of calculation that are of interest to someone following a diet plan. Calculators for the Basal Metabolic Rate are based on Mifflin et al. (1990) <doi:10.1093/ajcn/51.2.241> and McArdle, W. D., Katch, F. I., & Katch, V. L. (2010, ISBN:9780812109917).

This package provides a set of functions to visualize National Football League analysis in ggplot2 plots and gt tables.

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 package contains the functions for testing the spatial patterns (of segregation, spatial symmetry, association, disease clustering, species correspondence, and reflexivity) based on nearest neighbor relations, especially using contingency tables such as nearest neighbor contingency tables (Ceyhan (2010) <doi:10.1007/s10651-008-0104-x> and Ceyhan (2017) <doi:10.1016/j.jkss.2016.10.002> and references therein), nearest neighbor symmetry contingency tables (Ceyhan (2014) <doi:10.1155/2014/698296>), species correspondence contingency tables and reflexivity contingency tables (Ceyhan (2018) <doi:10.2436/20.8080.02.72> for two (or higher) dimensional data. The package also contains functions for generating patterns of segregation, association, uniformity in a multi-class setting (Ceyhan (2014) <doi:10.1007/s00477-013-0824-9>), and various non-random labeling patterns for disease clustering in two dimensional cases (Ceyhan (2014) <doi:10.1002/sim.6053>), and for visualization of all these patterns for the two dimensional data. The tests are usually (asymptotic) normal z-tests or chi-square tests.

Utilities and kinship information for behavior genetics and developmental research using the National Longitudinal Survey of Youth (NLSY; <https://www.nlsinfo.org/>).

Run simple direct gravitational N-body simulations. The package can access different external N-body simulators (e.g. GADGET-4 by Springel et al. (2021) <doi:10.48550/arXiv.2010.03567>), but also has a simple built-in simulator. This default simulator uses a variable block time step and lets the user choose between a range of integrators, including 4th and 6th order integrators for high-accuracy simulations. Basic top-hat smoothing is available as an option. The code also allows the definition of background particles that are fixed or in uniform motion, not subject to acceleration by other particles.

Estimates of coefficients of lasso penalized linear regression and generalized linear models subject to non-negativity constraints on the parameters using multiplicative iterative algorithm. Entire regularization path for a sequence of lambda values can be obtained. Functions are available for creating plots of regularization path, cross validation and estimating coefficients at a given lambda value. There is also provision for obtaining standard error of coefficient estimates.

Datasets for nlmixr2 and rxode2'. nlmixr2 is used for fitting and comparing 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>).

Density, distribution function, quantile function and random generation for the 3D Navarro, Frenk & White (NFW) profile. For details see Robotham & Howlett (2018) <arXiv:1805.09550>.

This package provides a graphical display of results from network meta-analysis (NMA). It is suitable for outcomes like odds ratio (OR), risk ratio (RR), risk difference (RD) and standardized mean difference (SMD). It also has an option to visually display and compare the surface under the cumulative ranking (SUCRA) of different treatments.

An implementation of the National Information Platforms for Nutrition or NiPN's analytic methods for assessing quality of anthropometric datasets that include measurements of weight, height or length, middle upper arm circumference, sex and age. The focus is on anthropometric status but many of the presented methods could be applied to other variables.

This package provides quality control (QC), normalization, and batch effect correction operations for NanoString nCounter data, Talhouk et al. (2016) <doi:10.1371/journal.pone.0153844>. Various metrics are used to determine which samples passed or failed QC. Gene expression should first be normalized to housekeeping genes, before a reference-based approach is used to adjust for batch effects. Raw NanoString data can be imported in the form of Reporter Code Count (RCC) files.