Performs Bayesian arm-based network meta-analysis for datasets with binary, continuous, and count outcomes
 (Zhang et al., 2014 <doi:10.1177/1740774513498322>;
  Lin et al., 2017 <doi:10.18637/jss.v080.i05>).

Bandwidth selector according to the Penalised Comparison to Overfitting (P.C.O.) 
             criterion as described in Varet, S., Lacour, C., Massart, P., Rivoirard, V., (2019)
             <https://hal.archives-ouvertes.fr/hal-02002275>. 
             It can be used with univariate and multivariate data.

An implementation of the parameter cascade method in Ramsay, J. O., Hooker,G., Campbell, D., and Cao, J. (2007) for estimating ordinary differential equation models with missing or complete observations. It combines smoothing method and profile estimation to estimate any non-linear dynamic system. The package also offers variance estimates for parameters of interest based on either bootstrap or Delta method.

Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. & Kiers H. A. L. (1992) <doi:10.1016/0169-7439(92)80100-I>). Several rotation and model selection options are provided.

Allows for nonparametric regression where one assumes that the signal is given by the sum of a piecewise constant function and a smooth function. More precisely, it implements the estimator PCpluS (piecewise constant plus smooth regression estimator) from Pein and Shah (2025) <doi:10.48550/arXiv.2112.03878>.

Implementation of the pattern recognition technique Principal
    Component Pursuit tailored to environmental health data, as described
    in Gibson et al (2022) <doi:10.1289/EHP10479>.

Set of functions for analysis of Principal Coordinates of Phylogenetic Structure (PCPS).

A collection of functions and data sets that support teaching
  a quantitative finance MS level course on Portfolio Construction and Risk
  Analysis, and the writing of a textbook for such a course.  The package is
  unique in providing several real-world data sets that may be used for problem
  assignments and student projects.  The data sets include cross-sections of
  stock data from the Center for Research on Security Prices, LLC (CRSP),
  corresponding factor exposures data from S&P Global, and several SP500 data
  sets.