Testing functions for Covariance Matrices. These tests include high-dimension homogeneity of covariance matrix testing described by Schott (2007) doi:10.1016/j.csda.2007.03.004 and high-dimensional one-sample tests of covariance matrix structure described by Fisher, et al. (2010) doi:10.1016/j.jmva.2010.07.004. Covariance matrix tests use C++ to speed performance and allow larger data sets.

Provides likelihood functions as defined by Fisher (1922) doi:10.1098/rsta.1922.0009 and a function that creates likelihood functions from density functions. The functions are meant to aid in education of likelihood based methods.

An expansion of R’s ‘stats’ random wishart matrix generation. This package allows the user to generate singular, Uhlig and Harald (1994) doi:10.1214/aos/1176325375, and pseudo wishart, Diaz-Garcia, et al.(1997) doi:10.1006/jmva.1997.1689, matrices. In addition the user can generate wishart matrices with fractional degrees of freedom, Adhikari (2008) doi:10.1061/(ASCE)0733-9399(2008)134:12(1029), commonly used in volatility modeling. Users can also use this package to create random covariance matrices.

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