The functions are designed to find the efficient mean-variance frontier or 
 portfolio weights for static portfolio (called  Markowitz portfolio) analysis in resource 
 economics or nature conservation. Using the nonlinear programming solver ('Rsolnp'), 
 this package deals with the quadratic minimization of the variance-covariances without 
 shorting (i.e., non-negative portfolio weights) studied in Ando and Mallory (2012) 
 <doi:10.1073/pnas.1114653109>. See the examples, testing versions, and more details from: 
 <https://github.com/ysd2004/portn>.

Following Sommer (2022) <https://mediatum.ub.tum.de/1658240>
    portfolio level risk estimates (e.g. Value at Risk, Expected
    Shortfall) are estimated by modeling each asset univariately by an
    ARMA-GARCH model and then their cross dependence via a Vine Copula
    model in a rolling window fashion. One can even condition on
    variables/time series at certain quantile levels to stress test the
    risk measure estimates.

Win ratio approach to partially ordered data, such as multivariate ordinal 
  responses under product (consensus) or prioritized order. Two-sample tests and multiplicative
  regression models are implemented (Mao, 2024, under revision).

Provides a set of basic tools for generating, analyzing, summarizing and visualizing finite partially ordered sets. In particular, it implements flexible and very efficient algorithms for the extraction of linear extensions and for the computation of mutual ranking probabilities and other user-defined functionals, over them. The package is meant as a computationally efficient "engine", for the implementation of data analysis procedures, on systems of multidimensional ordinal indicators and partially ordered data, in the spirit of Fattore, M. (2016) "Partially ordered sets and the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-015-1059-6>, and Fattore M. and Arcagni, A. (2018) "A reduced posetic approach to the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-016-1501-4>.