Three generalizations of the synthetic control method (which has 
    already an implementation in package 'Synth') are implemented: first, 
    'MSCMT' allows for using multiple outcome variables, second, time series 
    can be supplied as economic predictors, and third, a well-defined 
    cross-validation approach can be used.
    Much effort has been taken to make the implementation as stable as possible 
    (including edge cases) without losing computational efficiency.
    A detailed description of the main algorithms is given in 
    Becker and Klößner (2018) <doi:10.1016/j.ecosta.2017.08.002>.

Find common entities detected in both positive and negative
    ionization mode, delete this entity in the less sensible mode and combine both
    matrices.

Multiscale moving sum procedure for the detection of changes in expectation in univariate sequences. References - Multiscale change point detection via gradual bandwidth adjustment in moving sum processes (2021+), Tijana Levajkovic and Michael Messer.

Methods for analyzing and using quartets displayed on a collection 
 of gene trees, primarily to make inferences about the species tree or network 
 under the multi-species coalescent model. These include quartet hypothesis tests
 for the model, as developed by Mitchell et al. (2019) <doi:10.1214/19-EJS1576>, 
 simplex plots of quartet concordance factors as presented by Allman et al. (2020) 
 <doi:10.1101/2020.02.13.948083>, species tree inference methods based on quartet 
 distances of Rhodes (2019) <doi:10.1109/TCBB.2019.2917204> and Yourdkhani and 
 Rhodes (2019) <doi:10.1007/s11538-020-00773-4>, the NANUQ algorithm for inference 
 of level-1 species networks of Allman et al. (2019) <doi:10.1186/s13015-019-0159-2>, 
 and the TINNIK algorithm for inference of the tree of blobs of an arbitrary 
 network of Allman et al.(2022) <doi:10.1007/s00285-022-01838-9>. Software 
 announcement by Rhodes et al. (2020) <doi:10.1093/bioinformatics/btaa868>.

Statistical tests for validating multispecies coalescent gene tree simulators, using pairwise distances and rooted triple counts. Background is given by Allman, Banos, and Rhodes (2019) <arXiv:1908.01424>.