Found 181 packages in 0.02 seconds
Diversity Measures on Tripartite Graphs
Computing diversity measures on tripartite graphs. This package first implements a parametrized family of such diversity measures which apply on probability distributions. Sometimes called "True Diversity", this family contains famous measures such as the richness, the Shannon entropy, the Herfindahl-Hirschman index, and the Berger-Parker index. Second, the package allows to apply these measures on probability distributions resulting from random walks between the levels of tripartite graphs. By defining an initial distribution at a given level of the graph and a path to follow between the three levels, the probability of the walker's position within the final level is then computed, thus providing a particular instance of diversity to measure.
Provides a Function to Calculate Prize Winner Indices Based on Bibliometric Data
A function 'PWI()' that calculates prize winner indices based on bibliometric data is provided. The default is the 'Derek de Solla Price Memorial Medal'. Users can provide recipients of other prizes.
A Simple Data Science Challenge System
A simple data science challenge system using R Markdown and 'Dropbox' < https://www.dropbox.com/>. It requires no network configuration, does not depend on external platforms like e.g. 'Kaggle' < https://www.kaggle.com/> and can be easily installed on a personal computer.
Structured Covariances Estimators for Pairwise and Spatial Covariates
Implements estimators for structured covariance matrices in the
presence of pairwise and spatial covariates.
Metodiev, Perrot-Dockès, Ouadah, Fosdick, Robin, Latouche & Raftery (2025)
Regression and Classification Tools
Tools for linear, nonlinear and nonparametric regression and classification. Novel graphical methods for assessment of parametric models using nonparametric methods. One vs. All and All vs. All multiclass classification, optional class probabilities adjustment. Nonparametric regression (k-NN) for general dimension, local-linear option. Nonlinear regression with Eickert-White method for dealing with heteroscedasticity. Utilities for converting time series to rectangular form. Utilities for conversion between factors and indicator variables. Some code related to "Statistical Regression and Classification: from Linear Models to Machine Learning", N. Matloff, 2017, CRC, ISBN 9781498710916.
The Free Group
The free group in R; juxtaposition is represented by a
plus. Includes inversion, multiplication by a scalar,
group-theoretic power operation, and Tietze forms. To cite the
package in publications please use Hankin (2022)
The Exterior Calculus
Provides functionality for working with tensors, alternating
forms, wedge products, Stokes's theorem, and related concepts
from the exterior calculus. Uses 'disordR' discipline
(Hankin, 2022,
How to Add Two R Tables
Methods to "add" two R tables; also an alternative
interpretation of named vectors as generalized R tables, so that
c(a=1,b=2,c=3) + c(b=3,a=-1) will return c(b=5,c=3). Uses
'disordR' discipline (Hankin, 2022,
The Lorentz Transform in Relativistic Physics
The Lorentz transform in special relativity; also the gyrogroup structure of three-velocities. Performs active and passive transforms and has the ability to use units in which the speed of light is not unity. Includes some experimental functionality for celerity and rapidity. For general relativity, see the 'schwarzschild' package.
A Suite of Routines for Working with Jordan Algebras
A Jordan algebra is an algebraic object originally
designed to study observables in quantum mechanics. Jordan
algebras are commutative but non-associative; they satisfy the
Jordan identity. The package follows the ideas and notation of
K. McCrimmon (2004, ISBN:0-387-95447-3) "A Taste of Jordan
Algebras". To cite the package in publications, please use
Hankin (2023)