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The aim of the R package netCoin is to explore data structures using a number of statistical techniques that share the handling of interdependent variables. The main objective of this analysis is to detect events, characters, objects, attributes or characteristics that tend to appear together within a given set of scenarios. Its most notable feature is the combination of traditional multivariate statistical analysis and network analysis supported by topological graph theory. In addition, netCoin...

In randomized controlled trials of seriously ill patients, death is common and often defined as the primary endpoint. Increasingly, non-mortality outcomes such as functional outcomes are co-primary or secondary endpoints. Functional outcomes are not defined for patients who die, referred to as "truncation due to death", and among survivors, functional outcomes are often unobserved due to missed clinic visits or loss to follow-up. It is well known that if the functional outcomes "truncated due to...

We propose new statistical tools to analyze and to estimate archeological phases from the posterior distribution of a sequence of dates. All the functions are implemented in the R package ArchaeoPhases. The required inputs are simulated samples from the posterior distribution of the dates. Such Markov Chains Monte Carlo samples are provided, for instance, by ChronoModel or Oxcal, two softwares build for the chronological modeling of archeological dates. We give a practical introduction to the pa...

To extend the current implementation of copulas in MATLAB to non-elliptical distributions in arbitrary dimensions enabling for asymmetries in the tails, the toolbox HACopula provides functionality for modeling with hierarchical (or nested) Archimedean copulas. This includes their representation as MATLAB objects, evaluation, sampling, estimation and goodness-of-fit testing, as well as tools for their visual representation or computation of corresponding matrices of Kendall's tau and tail depende...

A wide range of chemical information is freely available online, including identifiers, experimental and predicted chemical properties. However, these data are scattered over various data sources and not easily accessible to researchers. Manual searching and downloading of such data is time-consuming and error-prone. We developed the open-source R package webchem that allows users to automatically query chemical data from currently 14 web sources. These cover a broad spectrum of information. The...

Cognitive diagnosis models (CDMs) have attracted increasing attention in educational measurement because of their potential to provide diagnostic feedback about students' strengths and weaknesses. This article introduces the feature-rich R package GDINA for conducting a variety of CDM analyses. Built upon a general model framework, a number of CDMs can be calibrated using the GDINA package. Functions are also available for evaluating model-data fit, detecting differential item functioning, valid...

An R package for computing the all-subsets regression problem is presented. The proposed algorithms are based on computational strategies recently developed. A novel algorithm for the best-subset regression problem selects subset models based on a predetermined criterion. The package user can choose from exact and from approximation algorithms. The core of the package is written in C++ and provides an efficient implementation of all the underlying numerical computations. A case study and benchma...

This paper introduces the funData R package as an object-oriented implementation of functional data. It implements a unified framework for dense univariate and multivariate functional data on one- and higher dimensional domains as well as for irregular functional data. The aim of this package is to provide a user-friendly, self-contained core toolbox for functional data, including important functionalities for creating, accessing and modifying functional data objects, that can serve as a basis f...

Sparse estimation via penalized likelihood (PL) is now a popular approach to learn the associations among a large set of variables. This paper describes an R package called lslx that implements PL methods for semi-confirmatory structural equation modeling (SEM). In this semi-confirmatory approach, each model parameter can be specified as free/fixed for theory testing, or penalized for exploration. By incorporating either a L1 or minimax concave penalty, the sparsity pattern of the parameter matr...

The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link. A flexible modeling framework for multiple ordinal measurements on the same subject is set up, which takes into consideration the dependence among the multiple observations by employing different error structures. Heterogeneity in the error structure across the subjects can be accounted for by the package, which allows for...

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