StatPerMeCo
Statistical Performance Measures to Evaluate Covariance Matrix Estimates
Statistical performance measures used in the econometric literature to evaluate conditional covariance/correlation matrix estimates (MSE, MAE, Euclidean distance, Frobenius distance, Stein distance, asymmetric loss function, eigenvalue loss function and the loss function defined in Eq. (4.6) of Engle et al. (2016) doi:10.2139/ssrn.2814555). Additionally, compute Eq. (3.1) and (4.2) of Li et al. (2016) doi:10.1080/07350015.2015.1092975 to compare the factor loading matrix. The statistical performance measures implemented have been previously used in, for instance, Laurent et al. (2012) doi:10.1002/jae.1248, Amendola et al. (2015) doi:10.1002/for.2322 and Becker et al. (2015) doi:10.1016/j.ijforecast.2013.11.007.
- Version0.1.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release04/14/2017
Team
Carlos Trucios
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