Browse Items (14 total)

Algebraic methods have a long history in statistics. Apart from the ubiquitous applications of linear algebra, the most visible manifestations of modern algebra in statistics
are found in the young field of algebraic statistics, which brings tools…

The random-effects or normal-normal hierarchical model is commonly utilized in a
wide range of meta-analysis applications. A Bayesian approach to inference is very attractive in this context, especially when a meta-analysis is based only on few…

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…

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)…

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…

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…

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…

Manifold optimization appears in a wide variety of computational problems in the applied sciences. In recent statistical methodologies such as sufficient dimension reduction
and regression envelopes, estimation relies on the optimization of…

We present the R package mgm for the estimation of k-order mixed graphical models (MGMs) and mixed vector autoregressive (mVAR) models in high-dimensional data.
These are a useful extensions of graphical models for only one variable type, since…

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…