Browse Items (17 total)

Optimization plays an important role in many methods routinely used in statistics,
machine learning and data science. Often, implementations of these methods rely on
highly specialized optimization algorithms, designed to be only applicable within…

The R add-on package FDboost is a flexible toolbox for the estimation of functional
regression models by model-based boosting. It provides the possibility to fit regression
models for scalar and functional response with effects of scalar as well as…

We present the R package PResiduals for residual analysis using the probability-scale
residual. This residual is well defined for a wide variety of outcome types and models, including some settings where other popular residuals are not applicable.…

Data analysis projects invariably involve a series of steps such as reading, cleaning,
summarizing and plotting data, statistical analysis and reporting. To facilitate reproducible research, rather than employing a relatively ad-hoc point-and-click…

Subset identification methods are used to select the subset of a covariate space over
which the conditional distribution of a response has certain properties – for example,
identifying types of patients whose conditional treatment effect is…

The R package AssocTests provides some procedures which are commonly used in
genetic association studies. These procedures are population stratification correction
through eigenvectors, principal coordinates of clusterings, Tracy-Widom test,…

Fractional factorial experiments often produce ambiguous results due to confounding
among the factors; as a consequence more than one model is consistent with the data.
Thus, the practical problem is how to choose additional runs in order to…

A large number of statistical decision problems in the social sciences and beyond can
be framed as a (contextual) multi-armed bandit problem. However, it is notoriously hard
to develop and evaluate policies that tackle these types of problems, and…

The BayesNetBP package has been developed for probabilistic reasoning and visualization in Bayesian networks with nodes that are purely discrete, continuous or mixed
(discrete and continuous). Probabilistic reasoning enables a user to absorb…

Disease spreading simulations are traditionally performed using coupled differential
equations. However, in the setting of metapopulations, most of the solutions provided by
this method do not account for the dynamic topography of subpopulations.…