An implementation of statistical tools for the analysis 
    of rotation-valued time series and functional data. It relies on 
    pre-existing quaternion data structure provided by the 'Eigen' 'C++' 
    library.

Data processing and visualizations for rodent vocalizations exported from
    'DeepSqueak'. These functions are compatible with the 'SqueakR' Shiny Dashboard,
    which can be used to visualize experimental results and analyses.

Fit linear and logistic regression models penalised with group-adaptive elastic net penalties.
  The group penalties correspond to groups of covariates defined by a co-data group set.
  The method accommodates inclusion of unpenalised covariates and overlapping groups.
  See Van Nee et al. (2021) <arXiv:2101.03875>.

A simulation-based tool made to help researchers to become familiar with
    multilevel variations, and to build up sampling designs for their study. 
    This tool has two main objectives: First, it provides an educational tool useful for students, 
    teachers and researchers who want to learn to use mixed-effects models. 
    Users can experience how the mixed-effects model framework can be used to understand 
    distinct biological phenomena by interactively exploring simulated multilevel data. 
    Second, it offers research opportunities to those who are already familiar with 
    mixed-effects models, as it enables the generation of data sets that users may download 
    and use for a range of simulation-based statistical analyses such as power 
    and sensitivity analysis of multilevel and multivariate data [Allegue, H., Araya-Ajoy, Y.G., Dingemanse, 
    N.J., Dochtermann N.A., Garamszegi, L.Z., Nakagawa, S., Reale, D., Schielzeth, H. and Westneat, D.F. (2016) 
    <doi: 10.1111/2041-210X.12659>].

Finds causal connections in precision data, finds lags and embeddings in 
  time series, guides training of neural networks and other smooth models, evaluates 
  their performance, gives a mathematically grounded answer to the over-training 
  problem.  Smooth regression is based on the Gamma test, which measures smoothness
  in a multivariate relationship.  Causal relations are smooth, noise is not.  
  'sr' includes the Gamma test and search techniques that use it. 
  References: Evans & Jones (2002) <doi:10.1098/rspa.2002.1010>, 
  AJ Jones (2004) <doi:10.1007/s10287-003-0006-1>.