Multivariate tools to analyze comparative data, i.e. a phylogeny and some traits measured for each taxa. The package contains functions to represent comparative data, compute phylogenetic proximities, perform multivariate analysis with phylogenetic constraints and test for the presence of phylogenetic autocorrelation. The package is described in Jombart et al (2010) <doi:10.1093/bioinformatics/btq292>.

Contains a 'shiny' application called AdEPro (Animation of Adverse Event Profiles) which (audio-)visualizes adverse events occurring in clinical trials. As this data is usually considered sensitive, this tool is provided as a stand-alone application that can be launched from any local machine on which the data is stored.

Designed for optimal use in performing fast, 
    accurate walking strides segmentation from high-density 
    data collected from a wearable accelerometer worn 
    during continuous walking activity.

Created to host raw accelerometry data sets and their derivatives which are used in the corresponding 'adept' package.

The main application concerns to a new robust optimization package with two major contributions. The first contribution refers to the assessment of the adequacy of probabilistic models through a combination of several statistics, which measure the relative quality of statistical models for a given data set. The second one provides a general purpose optimization method based on meta-heuristics functions for maximizing or minimizing an arbitrary objective function.

Data sets used in Cayuela and De la Cruz (2022, ISBN:978-84-8476-833-3).

Tools for the multiscale spatial analysis of multivariate data.
    Several methods are based on the use of a spatial weighting matrix and its
    eigenvector decomposition (Moran's Eigenvectors Maps, MEM). 
    Several approaches are described in the review Dray et al (2012)
    <doi:10.1890/11-1183.1>.

Methods to evaluate the performance characteristics of
  various point and interval estimators for optimal adaptive two-stage designs as described
  in Meis et al. (2024) <doi:10.1002/sim.10020>.
  Specifically, this package is written to work with trial designs created by the 'adoptr' package
  (Kunzmann et al. (2021) <doi:10.18637/jss.v098.i09>; Pilz et al. (2021) <doi:10.1002/sim.8953>)).
  Apart from the a priori evaluation of performance characteristics, this package also allows for the
  evaluation of the implemented estimators on real datasets, and it implements methods
  to calculate p-values.