R-universe - astamm (Aymeric Stamm)

nloptr - R Interface to NLopt

Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/> for more information on the available algorithms. Building from included sources requires 'CMake'. On Linux and 'macOS', if a suitable system build of NLopt (2.7.0 or later) is found, it is used; otherwise, it is built from included sources via 'CMake'. On Windows, NLopt is obtained through 'rwinlib' for 'R <= 4.1.x' or grabbed from the appropriate toolchain for 'R >= 4.2.0'.

Last updated

cpp

16.87 score 114 stars 2.0k dependents 1.5k scripts 571k downloads

flipr - Flexible Inference via Permutations in R

A flexible permutation framework for making inference such as point estimation, confidence intervals or hypothesis testing, on any kind of data, be it univariate, multivariate, or more complex such as network-valued data, topological data, functional data or density-valued data.

Last updated

quartocpp

7.02 score 6 stars 2 dependents 48 scripts 225 downloads

roahd - Robust Analysis of High Dimensional Data

A collection of methods for the robust analysis of univariate and multivariate functional data, possibly in high-dimensional cases, and hence with attention to computational efficiency and simplicity of use. See the R Journal publication of Ieva et al. (2019) <doi:10.32614/RJ-2019-032> for an in-depth presentation of the 'roahd' package. See Aleman-Gomez et al. (2021) <arXiv:2103.08874> for details about the concept of depthgram.

Last updated

6.48 score 3 stars 2 dependents 166 scripts 341 downloads

phutil - Persistence Homology Utilities

A low-level package for hosting persistence data. It is part of the 'TDAverse' suite of packages, which is designed to provide a collection of packages for enabling machine learning and data science tasks using persistent homology. Implements a class for hosting persistence data, a number of coercers from and to already existing and used data structures from other packages and functions to compute distances between persistence diagrams. A formal definition and study of bottleneck and Wasserstein distances can be found in Bubenik, Scott and Stanley (2023) <doi:10.1007/s41468-022-00103-8>. Their implementation in 'phutil' relies on the 'C++' Hera library developed by Kerber, Morozov and Nigmetov (2017) <doi:10.1145/3064175>.

Last updated

quartocppopenmp

6.23 score 2 dependents 28 scripts 656 downloads

fdacluster - Joint Clustering and Alignment of Functional Data

Implementations of the k-means, hierarchical agglomerative and DBSCAN clustering methods for functional data which allows for jointly aligning and clustering curves. It supports functional data defined on one-dimensional domains but possibly evaluating in multivariate codomains. It supports functional data defined in arrays but also via the 'fd' and 'funData' classes for functional data defined in the 'fda' and 'funData' packages respectively. It currently supports shift, dilation and affine warping functions for functional data defined on the real line and uses the SRVF framework to handle boundary-preserving warping for functional data defined on a specific interval. Main reference for the k-means algorithm: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment for curve clustering" <doi:10.1016/j.csda.2009.12.008>. Main reference for the SRVF framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013) "Generative models for functional data using phase and amplitude separation" <doi:10.1016/j.csda.2012.12.001>.

Last updated

openblascppopenmp

6.18 score 7 stars 1 dependents 36 scripts 301 downloads

fdatest - Interval Wise Testing for Functional Data

Implementation of local inferential (domain-selection) procedures for functional data in different frameworks (one- and two-sample tests, ANOVA, linear models). The current version of the package requires functional data evaluated on a common uniform grid or objects of class 'fd' as produced by the 'fda' package and provides the adjusted and unadjusted p-value functions based on nonparametric local tests. The package provides tools for visualization: (i) the p-value heatmap, the plot of the p-value functions and the plot of the functional data.

Last updated

cpp

4.81 score 3 dependents 48 scripts 351 downloads

rgeomstats - Interface to 'Geomstats'

Provides an interface to the Python package 'Geomstats' authored by Miolane et al. (2020) <arXiv:2004.04667>.

Last updated

3.78 score 4 stars 1 dependents 5 scripts 185 downloads

squat - Statistics for Quaternion Temporal Data

An implementation of statistical tools for the analysis of rotation-valued time series and functional data. It relies on pre-existing quaternion data structure provided by the 'Eigen' 'C++' library.

Last updated

cppopenmp

3.48 score 2 stars 7 scripts 224 downloads

nevada - Network-Valued Data Analysis

A flexible statistical framework for network-valued data analysis. It leverages the complexity of the space of distributions on graphs by using the permutation framework for inference as implemented in the 'flipr' package. Currently, only the two-sample testing problem is covered and generalization to k samples and regression will be added in the future as well. It is a 4-step procedure where the user chooses a suitable representation of the networks, a suitable metric to embed the representation into a metric space, one or more test statistics to target specific aspects of the distributions to be compared and a formula to compute the permutation p-value. Two types of inference are provided: a global test answering whether there is a difference between the distributions that generated the two samples and a local test for localizing differences on the network structure. The latter is assumed to be shared by all networks of both samples. References: Lovato, I., Pini, A., Stamm, A., Vantini, S. (2020) "Model-free two-sample test for network-valued data" <doi:10.1016/j.csda.2019.106896>; Lovato, I., Pini, A., Stamm, A., Taquet, M., Vantini, S. (2021) "Multiscale null hypothesis testing for network-valued data: Analysis of brain networks of patients with autism" <doi:10.1111/rssc.12463>.

Last updated

quartoopenblascpp

3.48 score 6 stars 7 scripts 205 downloads

rvtk - Bindings for the Visualization Toolkit ('VTK')

Provides pre-compiled static 'VTK' libraries and headers so that downstream R packages can link against the Visualization Toolkit without requiring users to install 'VTK' manually. On all platforms the package first honours a user-supplied 'VTK_DIR' environment variable. On macOS it then tries 'Homebrew', followed by 'pkg-config'. On Linux it tries 'pkg-config' and well-known system prefixes ('/usr', '/usr/local'). If no suitable system installation is found on macOS or Linux, pre-built static libraries are downloaded automatically from the package's GitHub releases for x86_64 and aarch64. On Windows the package tries 'VTK_DIR', then 'Rtools45' 'pacman', then common 'MSYS2' prefixes, accepting both static ('.a') and shared ('.dll.a' import libs + DLLs) installations. When shared libraries are used, the VTK DLLs are staged in 'inst/vtk-dlls/' and an '.onLoad' hook prepends that directory to PATH via 'Sys.setenv()' when the package is loaded, and restored in '.onUnload()'. The pre-built fallback downloads static libraries by default; set 'VTK_LINK_TYPE=shared' before installation to download the DLL build instead. The pre-built bundles include the following VTK modules (plus their transitive dependencies): 'VTK_IOLegacy', 'VTK_IOXML', 'VTK_IOCore', 'VTK_CommonCore', and 'VTK_CommonDataModel'. Note that on Windows 'VTK_IONetCDF', 'VTK_IOHDF', 'VTK_GeovisCore', and 'VTK_RenderingCore' are additionally disabled because 'netcdf' and 'libproj' are not available in the 'Rtools45' 'static.posix' sysroot. Downstream packages can declare 'Imports: rvtk' and obtain the correct compiler and linker flags at install time via rvtk::CppFlags() and rvtk::LdFlagsFile(), optionally restricting linking to a subset of modules via the 'modules' argument. A convenience helper use_rvtk() (in the spirit of the 'usethis' package) automates the full setup of a downstream package: it adds 'rvtk' to 'Imports' in 'DESCRIPTION' and writes all files required to resolve VTK flags at install time ('src/Makevars', 'src/Makevars.win', 'tools/configure.R', and 'R/rvtk_imports.R'), and keeps generated build artefacts out of version control.

Last updated

3.40 score 3 scripts 251 downloads

inphr - Statistical Inference for Persistence Homology Data

A set of functions for performing null hypothesis testing on samples of persistence diagrams using the theory of permutations. Currently, only two-sample testing is implemented. Inputs can be either samples of persistence diagrams themselves or vectorizations. In the former case, they are embedded in a metric space using either the Bottleneck or Wasserstein distance. In the former case, persistence data becomes functional data and inference is performed using tools available in the 'fdatest' package. Main reference for the interval-wise testing method: Pini A., Vantini S. (2017) "Interval-wise testing for functional data" <doi:10.1080/10485252.2017.1306627>. Main reference for inference on populations of networks: Lovato, I., Pini, A., Stamm, A., & Vantini, S. (2020) "Model-free two-sample test for network-valued data" <doi:10.1016/j.csda.2019.106896>.

Last updated

3.40 score 1 stars 7 scripts 208 downloads

midi - Microstructure Information from Diffusion Imaging

An implementation of a taxonomy of models of restricted diffusion in biological tissues parametrized by the tissue geometry (axis, diameter, density, etc.). This is primarily used in the context of diffusion magnetic resonance (MR) imaging to model the MR signal attenuation in the presence of diffusion gradients. The goal is to provide tools to simulate the MR signal attenuation predicted by these models under different experimental conditions. The package feeds a companion 'shiny' app available at <https://midi-pastrami.apps.math.cnrs.fr> that serves as a graphical interface to the models and tools provided by the package. Models currently available are the ones in Neuman (1974) <doi:10.1063/1.1680931>, Van Gelderen et al. (1994) <doi:10.1006/jmrb.1994.1038>, Stanisz et al. (1997) <doi:10.1002/mrm.1910370115>, Soderman & Jonsson (1995) <doi:10.1006/jmra.1995.0014> and Callaghan (1995) <doi:10.1006/jmra.1995.1055>.

Last updated

3.32 score 1 stars 14 scripts 194 downloads

fiber - S7 Data Structures for Diffusion MRI Tractography

Provides three S7 classes — streamline, bundle, and bundle_set — for representing diffusion MRI tractography data in R, together with a concise set of methods for computing shape descriptors (arc-length, curvature, torsion, sinuosity), the Hausdorff distance between streamlines, arc-length reparametrization of streamlines and bundles onto uniform grids, combination of streamlines or bundles into a single bundle, combination of bundles from multiple subjects or sessions into a bundle_set, and coercion to and from the dwiFiber S4 class of the 'dti' package. See Dell'Acqua, F., Descoteaux, M. and Leemans, A. (2024) "Handbook of Diffusion MR Tractography" <doi:10.1016/C2018-0-02520-7> for more about the mathematical and computational underpinnings of diffusion MRI tractography.

Last updated

cpp

3.18 score 1 stars

distops - Usual Operations for Distance Matrices in R

It provides the subset operator for dist objects and a function to compute medoid(s) that are fully parallelized leveraging the 'RcppParallel' package. It also provides functions for package developers to easily implement their own parallelized dist() function using a custom 'C++'-based distance function.

Last updated

cpp

3.00 score 2 stars 3 scripts 180 downloads

mupet - Multiclass Performance Evaluation Toolkit

Implementation of custom 'tidymodels' metrics for multi-class prediction models with a single negative class. Currently are implemented macro-average sensitivity and specificity as in Mortaz, Ebrahim (2020) "Imbalance accuracy metric for model selection in multi-class imbalance classification problems” <doi:10.1016/j.knosys.2020.106490> and a generalized weighted Youden index as in Li, D.L., Shen F., Yin Y., Peng J.X and Chen P.Y. (2013) “Weighted Youden index and its two-independent-sample comparison based on weighted sensitivity and specificity” <doi:10.3760/cma.j.issn.0366-6999.20123102>.

Last updated

2.70 score 1 scripts 155 downloads

rvtk - Bindings for the Visualization Toolkit ('VTK')

Last updated

1.70 score