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>.

Version: 0.1.0
Published: 2017-04-14
Author: Carlos Trucios
Maintainer: Carlos Trucios <ctrucios at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: StatPerMeCo results

Downloads:

Reference manual: StatPerMeCo.pdf
Package source: StatPerMeCo_0.1.0.tar.gz
Windows binaries: r-devel: StatPerMeCo_0.1.0.zip, r-release: StatPerMeCo_0.1.0.zip, r-oldrel: StatPerMeCo_0.1.0.zip
OS X El Capitan binaries: r-release: StatPerMeCo_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: StatPerMeCo_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=StatPerMeCo to link to this page.