Found 1169 packages in 0.03 seconds
Tidy Geospatial Networks
Provides a tidy approach to spatial network analysis, in the form of classes and functions that enable a seamless interaction between the network analysis package 'tidygraph' and the spatial analysis package 'sf'.
Fast, Dependency-Free Geodesic Distance Calculations
Dependency-free, ultra fast calculation of geodesic
distances. Includes the reference nanometre-accuracy geodesic
distances of Karney (2013)
Fast Multivariate Normal and Student's t Methods
Provides computationally efficient tools related to the multivariate normal and Student's t distributions. The main functionalities are: simulating multivariate random vectors, evaluating multivariate normal or Student's t densities and Mahalanobis distances. These tools are very efficient thanks to the use of C++ code and of the OpenMP API.
Web Application Framework for R
Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.
The Lawson-Hanson Algorithm for Non-Negative Least Squares (NNLS)
An R interface to the Lawson-Hanson implementation of an algorithm for non-negative least squares (NNLS). Also allows the combination of non-negative and non-positive constraints.
Phylogenetic Linear Regression
Provides functions for fitting phylogenetic linear models and phylogenetic generalized linear models. The computation uses an algorithm that is linear in the number of tips in the tree. The package also provides functions for simulating continuous or binary traits along the tree. Other tools include functions to test the adequacy of a population tree.
Record Linkage Toolkit
Functions to assist in performing probabilistic record linkage and
deduplication: generating pairs, comparing records, em-algorithm for
estimating m- and u-probabilities
(I. Fellegi & A. Sunter (1969)
Miscellaneous, Analytic R Kernels
Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.
Compositional Data Analysis
Provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations) in the way proposed by J. Aitchison and V. Pawlowsky-Glahn.
R Interface to Stan
User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.