A set of simple functions that transforms longitudinal
    data to estimate the cosinor linear model as described in Tong (1976).
    Methods are given to summarize the mean, amplitude and acrophase, to
    predict the mean annual outcome value, and to test the coefficients.

Statistical procedures for calculating population–mean cosinor, non–stationary cosinor, estimation of best–fitting period, tests of population rhythm differences and more. See Cornélissen, G. (2014). <doi:10.1186/1742-4682-11-16>.

A data package with 2 main package variables: 'signature' and 'etiology'. 
     The 'signature' variable contains the latest mutational signature profiles 
     released on COSMIC <https://cancer.sanger.ac.uk/signatures/> for 3 mutation
     types:
     * Single base substitutions in the context of preceding and following bases,
     * Doublet base substitutions, and
     * Small insertions and deletions.
    The 'etiology' variable provides the known or hypothesized causes of signatures. 
    'cosmicsig' stands for COSMIC signatures. Please run ?'cosmicsig' for more
    information.

Package encapsulates standard expressions for distances, times, luminosities, and other quantities useful in observational cosmology, including molecular line observations.  Currently coded for a flat universe only.

Makes univariate, multivariate, or random fields simulations precise and simple. Just select the desired time series or random fields’ properties and it will do the rest. CoSMoS is based on the framework described in Papalexiou (2018, <doi:10.1016/j.advwatres.2018.02.013>), extended for random fields in Papalexiou and Serinaldi (2020, <doi:10.1029/2019WR026331>), and further advanced in Papalexiou et al. (2021, <doi:10.1029/2020WR029466>) to allow fine-scale space-time simulation of storms (or even cyclone-mimicking fields).

The COSSO regularization method automatically
        estimates and selects important function components by a
        soft-thresholding penalty in the context of smoothing spline
        ANOVA models. Implemented models include mean regression,
        quantile regression, logistic regression and the Cox regression
        models.