Uses both ridge and lasso penalties (and extensions) to penalize
    specific parameters in structural equation models. The package offers additional
    cost functions, cross validation, and other extensions beyond traditional structural
    equation models. Also contains a function to perform exploratory mediation (XMed).

Computes linear Bayesian spectral estimates from multirate	data for second-order stationary time series. Provides credible intervals and methods for plotting various spectral estimates. Please see the paper `Should we sample a time series more frequently?' (doi below) for a full description of and motivation for the methodology.

For a sequence of event occurence times, we are interested in
  finding subsequences in it that are too "regular". We define regular as being
  significantly different from a homogeneous Poisson process. The departure from
  the Poisson process is measured using a L1 distance. See Di and Perlman 2007
  for more details.

In repeated measures studies with extreme large or small values it is common 
  that the subjects measurements on average are closer to the mean of the basic population. 
  Interpreting possible changes in the mean in such situations can lead to biased results 
  since the values were not randomly selected, they come from truncated sampling.
  This method allows to estimate the range of means where treatment effects are likely to occur 
  when regression toward the mean is present. 
  Ostermann, T., Willich, Stefan N. & Luedtke, Rainer. (2008). Regression toward the mean - a detection method for unknown population mean based on Mee and Chua's algorithm. BMC Medical Research Methodology.<doi:10.1186/1471-2288-8-52>.

Tools for linear, nonlinear and nonparametric regression
             and classification.  Novel graphical methods for assessment 
             of parametric models using nonparametric methods. One 
             vs. All and All vs. All multiclass classification, optional
             class probabilities adjustment.  Nonparametric regression 
             (k-NN) for general dimension, local-linear option.  Nonlinear 
             regression with Eickert-White method for dealing with 
             heteroscedasticity.  Utilities for converting time series
             to rectangular form.  Utilities for conversion between
             factors and indicator variables.  Some code related to
             "Statistical Regression and Classification: from Linear
             Models to Machine Learning", N. Matloff, 2017, CRC,
             ISBN 9781498710916.