Browse Items (12 total)

Analysis of dose-response data is an important step in many scientific disciplines,
including but not limited to pharmacology, toxicology, and epidemiology. The R package
drda is designed to facilitate the analysis of dose-response data by…

Disaggregation modeling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common,
leading to an increasing demand for modeling frameworks that can deal with this…

Quantile-quantile (Q-Q) plots are often difficult to interpret because it is unclear
how large the deviation from the theoretical distribution must be to indicate a lack of
fit. Most Q-Q plots could benefit from the addition of meaningful global…

This article illustrates intRinsic, an R package that implements novel state-of-the-art
likelihood-based estimators of the intrinsic dimension of a dataset, an essential quantity
for most dimensionality reduction techniques. In order to make these…

The lasso and elastic net are popular regularized regression models for supervised
learning. Friedman, Hastie, and Tibshirani (2010) introduced a computationally efficient
algorithm for computing the elastic net regularization path for ordinary…

The study of non-stationary behavior in the extremes is important to analyze data
in environmental sciences, climate, finance, or sports. As an alternative to the classical
extreme value theory, this analysis can be based on the study of…

The bayesTFR package for R provides a set of functions to produce probabilistic projections of the total fertility rates for all countries, and is widely used, including as part
of the basis for the United Nations official population projections for…

The R package MLGL, standing for multi-layer group-Lasso, implements a new procedure of variable selection in the context of redundancy between explanatory variables,
which holds true with high-dimensional data. A sparsity assumption is made that…

Network meta-analysis compares different interventions for the same condition, by
combining direct and indirect evidence derived from all eligible studies. Network metaanalysis has been increasingly used by applied scientists and it is a major…

Many longitudinal studies collect data that have irregular observation times, often
requiring the application of linear mixed models with time-varying outcomes. This paper
presents an alternative that splits the quantitative analysis into two…