Found 47 packages in 0.02 seconds
Use LaTeX Expressions in Plots
Parses and converts LaTeX math formulas to R's plotmath expressions, used to enter mathematical formulas and symbols to be rendered as text, axis labels, etc. throughout R's plotting system.
Simulation and Inference for Stochastic Differential Equations
Companion package to the book Simulation and Inference for Stochastic Differential Equations With R Examples, ISBN 978-0-387-75838-1, Springer, NY.
Coarsened Exact Matching
Implementation of the Coarsened Exact Matching algorithm discussed
along with its properties in
Iacus, King, Porro (2011)
Nash Optimal Party Positions
Estimation of party/candidate ideological positions that correspond to a Nash equilibrium along a one-dimensional space.
A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
Ultrasound Tongue Imaging in R
It provides functions for processing Articulate Assistant Advanced™ (AAA) export files and plot tongue contour data from any system.
Estimate Procedure in Case of First Order Autocorrelation
Solve first order autocorrelation problems using an iterative method. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal as default). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals.
Consensus Clustering of Omic Data
Procedures to perform consensus clustering starting from a dissimilarity matrix or a data matrix. It's allowed to select if the subsampling has to be by samples or features. In case of computational heavy load, the procedures can run in parallel.
Libreria Del Laboratorio Di Statistica Con R
Insieme di funzioni di supporto al volume "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. This package contains sets of functions defined in "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. Function names and docs are in italian as well.
Knowledge Discovery by Accuracy Maximization
An unsupervised and semi-supervised learning algorithm that performs feature extraction
from noisy and high-dimensional data. It facilitates identification of patterns representing underlying
groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA.