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  "Title": "Statistical Performance Measures to Evaluate Covariance Matrix\nEstimates",
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  "Date": "2017-04-13",
  "Author": "Carlos Trucios",
  "Maintainer": "Carlos Trucios <ctrucios@gmail.com>",
  "Description": "Statistical performance measures used in the econometric\nliterature to evaluate conditional covariance/correlation\nmatrix estimates (MSE, MAE, Euclidean distance, Frobenius\ndistance, Stein distance, asymmetric loss function, eigenvalue\nloss function and the loss function defined in Eq. (4.6) of\nEngle et al. (2016) <doi:10.2139/ssrn.2814555>). Additionally,\ncompute Eq. (3.1) and (4.2) of Li et al. (2016)\n<doi:10.1080/07350015.2015.1092975> to compare the factor\nloading matrix. The statistical performance measures\nimplemented have been previously used in, for instance, Laurent\net al. (2012) <doi:10.1002/jae.1248>, Amendola et al. (2015)\n<doi:10.1002/for.2322> and Becker et al. (2015)\n<doi:10.1016/j.ijforecast.2013.11.007>.",
  "License": "GPL (>= 2)",
  "Note": "The author acknowledges financial support from Sao Paulo Research\nFoundation (FAPESP) grant 2016/18599-4",
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  "Date/Publication": "2017-04-14 17:05:37 UTC",
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      "title": "Asymmetric loss function",
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      "title": "Mean Absolute Error",
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