Browse Items (15 total)

It has been fourteen years since the first edition of R Graphics was published (Murrell 2006)
and eight since the second one was released (Murrell 2012). For readers, like me, who read
the first edition of R Graphics but skipped the second one,…

gdpc is an R package for the computation of the generalized dynamic principal components proposed in Peña and Yohai (2016). In this paper, we briefly introduce the problem
of dynamical principal components, propose a solution based on a…

With the rising popularity of web surveys and the increasing use of paradata by survey
methodologists, assessing information stored in user agent strings becomes inevitable.
These data contain meaningful information about the browser, operating…

Prediction rule ensembles (PREs) are sparse collections of rules, offering highly interpretable regression and classification models. This paper shows how they can be fitted
using function pre from R package pre, which derives PREs largely through…

multiplex is a computer program that provides algebraic tools for the analysis of
multiple network structures within the R environment. Apart from the possibility to create
and manipulate multivariate data representing multiplex, signed, and…

Statistical procedures such as Bayes factor model selection and Bayesian model averaging require the computation of normalizing constants (e.g., marginal likelihoods). These
normalizing constants are notoriously difficult to obtain, as they usually…

Spatial survival analysis has received a great deal of attention over the last 20 years
due to the important role that geographical information can play in predicting survival.
This paper provides an introduction to a set of programs for…

The Oja median is one of several extensions of the univariate median to the multivariate case. It has many desirable properties, but is computationally demanding. In this
paper, we first review the properties of the Oja median and compare it to…

We discuss the R package SQUAREM for accelerating iterative algorithms which exhibit slow, monotone convergence. These include the well-known expectation-maximization
algorithm, majorize-minimize (MM), and other EM-like algorithms such as…

Multiobjective evolutionary algorithms based on decomposition (MOEA/D) represent
a widely used class of population-based metaheuristics for the solution of multicriteria
optimization problems. We introduce the MOEADr package, which offers many of…