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) ; Iacus, King, Porro (2012) and Iacus, King, Porro (2019) .

Iterated Function Systems

Iterated Function Systems Estimator as in Iacus and La Torre (2005) .

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.

Nash Optimal Party Positions

Estimation of party/candidate ideological positions that correspond to a Nash equilibrium along a one-dimensional space.

Generalized Weighted Quantile Sum Regression

Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) ), a random subset implementation of WQS (Curtin et al. (2019) ), a repeated holdout validation WQS (Tanner et al. (2019) ) and a WQS with 2 indices (Renzetti et al. (2023) ) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.

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.

Competitive Gene Sets Test with the Mann-Whitney-Wilcoxon Test

Friendly implementation of the Mann-Whitney-Wilcoxon test for competitive gene set enrichment analysis.

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.