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The techniques developed in\nBodnar et al. (2018 , 2019\n, 2020\n, 2021\n) are central to the\npackage. They provide simple and feasible estimators and tests\nfor optimal portfolio weights, which are applicable for 'large\np and large n' situations where p is the portfolio dimension\n(number of stocks) and n is the sample size. The package also\nincludes tools for constructing portfolios based on shrinkage\nestimators of the mean vector and covariance matrix as well as\na new Bayesian estimator for the Markowitz efficient frontier\nrecently developed by Bauder et al. 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