Browse Items (15 total)

Multiplex social networks are characterized by a common set of actors connected
through multiple types of relations. The multinet package provides a set of R functions
to analyze multiplex social networks within the more general framework of…

The INLAMSM package for the R programming language provides a collection of
multivariate spatial models for lattice data that can be used with the INLA package for
Bayesian inference. The multivariate spatial models implemented include different…

Conformal predictors estimate the reliability of outcomes made by supervised machine
learning models. Instead of a point value, conformal prediction defines an outcome region
that meets a user-specified reliability threshold. Provided that the data…

This paper describes the R package EpiILMCT, which allows users to study the spread
of infectious disease using continuous time individual level models (ILMs). The package provides tools for simulation from continuous time ILMs that are based on…

“Optimal cutpoints” for binary classification tasks are often established by testing
which cutpoint yields the best discrimination, for example the Youden index, in a specific
sample. This results in “optimal” cutpoints that are highly variable and…

Multivariate time series observations are increasingly common in multiple fields of
science but the complex dependencies of such data often translate into intractable models
with large number of parameters. An alternative is given by first reducing…

FRK is an R software package for spatial/spatio-temporal modeling and prediction
with large datasets. It facilitates optimal spatial prediction (kriging) on the most commonly used manifolds (in Euclidean space and on the surface of the sphere), for…

An increasing number of time-consuming simulators exhibit a complex noise structure
that depends on the inputs. For conducting studies with limited budgets of evaluations,
new surrogate methods are required in order to simultaneously model the mean…

We present mexhaz, an R package for fitting flexible hazard-based regression models
with the possibility to add time-dependent effects of covariates and to account for a twolevel hierarchical structure in the data through the inclusion of a normally…

The MixGHD package for R performs model-based clustering, classification, and discriminant analysis using the generalized hyperbolic distribution (GHD). This approach
is suitable for data that can be considered a realization of a (multivariate)…