Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 168 packages in 0.06 seconds

elliptic — by Robin K. S. Hankin, 6 years ago

Weierstrass and Jacobi Elliptic Functions

A suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions.

spray — by Robin K. S. Hankin, 5 months ago

Sparse Arrays and Multivariate Polynomials

Sparse arrays interpreted as multivariate polynomials. Uses 'disordR' discipline (Hankin, 2022, ). To cite the package in publications please use Hankin (2022) .

slopes — by Robin Lovelace, 4 days ago

Calculate Slopes of Roads, Rivers and Trajectories

Calculates the slope (longitudinal gradient or steepness) of linear geographic features such as roads (for more details, see Ariza-López et al. (2019) ) and rivers (for more details, see Cohen et al. (2018) ). It can use local Digital Elevation Model (DEM) data or download DEM data via the 'ceramic' package. The package also provides functions to add elevation data to linestrings and visualize elevation profiles.

alluvial — by Michal Bojanowski, 9 years ago

Alluvial Diagrams

Creating alluvial diagrams (also known as parallel sets plots) for multivariate and time series-like data.

rakeR — by Phil Mike Jones, 8 years ago

Easy Spatial Microsimulation (Raking) in R

Functions for performing spatial microsimulation ('raking') in R.

simDAG — by Robin Denz, 3 days ago

Simulate Data from a DAG and Associated Node Information

Simulate complex data from a given directed acyclic graph and information about each individual node. Root nodes are simply sampled from the specified distribution. Child Nodes are simulated according to one of many implemented regressions, such as logistic regression, linear regression, poisson regression and more. Also includes a comprehensive framework for discrete-time simulation, which can generate even more complex longitudinal data. For more details, see Robin Denz, Nina Timmesfeld (2025) .

ROOPSD — by Yoann Robin, 2 years ago

R Object Oriented Programming for Statistical Distribution

Statistical distribution in OOP (Object Oriented Programming) way. This package proposes a R6 class interface to classic statistical distribution, and new distributions can be easily added with the class AbstractDist. A useful point is the generic fit() method for each class, which uses a maximum likelihood estimation to find the parameters of a dataset, see, e.g. Hastie, T. and al (2009) . Furthermore, the rv_histogram class gives a non-parametric fit, with the same accessors that for the classic distribution. Finally, three random generators useful to build synthetic data are given: a multivariate normal generator, an orthogonal matrix generator, and a symmetric positive definite matrix generator, see Mezzadri, F. (2007) .

optiSolve — by Robin Wellmann, 4 years ago

Linear, Quadratic, and Rational Optimization

Solver for linear, quadratic, and rational programs with linear, quadratic, and rational constraints. A unified interface to different R packages is provided. Optimization problems are transformed into equivalent formulations and solved by the respective package. For example, quadratic programming problems with linear, quadratic and rational constraints can be solved by augmented Lagrangian minimization using package 'alabama', or by sequential quadratic programming using solver 'slsqp'. Alternatively, they can be reformulated as optimization problems with second order cone constraints and solved with package 'cccp'.

osrm — by Timothée Giraud, a year ago

Interface Between R and the OpenStreetMap-Based Routing Service OSRM

An interface between R and the 'OSRM' API. 'OSRM' is a routing service based on 'OpenStreetMap' data. See < http://project-osrm.org/> for more information. This package enables the computation of routes, trips, isochrones and travel distances matrices (travel time and kilometric distance).

calibrator — by Robin K. S. Hankin, 6 years ago

Bayesian Calibration of Complex Computer Codes

Performs Bayesian calibration of computer models as per Kennedy and O'Hagan 2001. The package includes routines to find the hyperparameters and parameters; see the help page for stage1() for a worked example using the toy dataset. A tutorial is provided in the calex.Rnw vignette; and a suite of especially simple one dimensional examples appears in inst/doc/one.dim/.