Implements the novel testing approach by Janitza et al.(2015)
    <http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-25587-4>
    for the permutation variable importance measure in a random forest and the
    PIMP-algorithm by Altmann et al.(2010) <doi:10.1093/bioinformatics/btq134>.
    Janitza et al.(2015) <http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-25587-4>
    do not use the "standard" permutation variable
    importance but the cross-validated permutation variable
    importance for the novel test approach. The cross-validated
    permutation variable importance is not based on the out-of-bag
    observations but uses a similar strategy which is inspired by
    the cross-validation procedure. The novel test approach can be
    applied for classification trees as well as for regression
    trees. However, the use of the novel testing approach has not
    been tested for regression trees so far, so this routine is
    meant for the expert user only and its current state is rather
    experimental.

Provides templates and functions to simplify the production and maintenance of curriculum vitae.

Provides fitting routines for four versions of the
        Vitality family of mortality models.

Provides a versatile range of functions, including exploratory data analysis, time-series analysis, organizational network analysis, and data validation, whilst at the same time implements a set of best practices in analyzing and visualizing data specific to 'Microsoft Viva Insights'.

Analysis of minor alleles in Illumina sequencing data of viral
    genomes. Functions in 'vivaldi' primarily operate on vcf files.

A suite of plots for displaying variable importance and two-way variable interaction jointly. Can also display partial dependence plots laid out in a pairs plot or 'zenplots' style.

Provides an easy to calculate local variable importance measure based on Ceteris Paribus profile 
  and global variable importance measure based on Partial Dependence Profiles.