Package: StatPerMeCo 0.1.0
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>.
Authors:
StatPerMeCo_0.1.0.tar.gz
StatPerMeCo_0.1.0.zip(r-4.5)StatPerMeCo_0.1.0.zip(r-4.4)StatPerMeCo_0.1.0.zip(r-4.3)
StatPerMeCo_0.1.0.tgz(r-4.4-any)StatPerMeCo_0.1.0.tgz(r-4.3-any)
StatPerMeCo_0.1.0.tar.gz(r-4.5-noble)StatPerMeCo_0.1.0.tar.gz(r-4.4-noble)
StatPerMeCo_0.1.0.tgz(r-4.4-emscripten)StatPerMeCo_0.1.0.tgz(r-4.3-emscripten)
StatPerMeCo.pdf |StatPerMeCo.html✨
StatPerMeCo/json (API)
# Install 'StatPerMeCo' in R: |
install.packages('StatPerMeCo', repos = c('https://ctruciosm.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:e8735fa477. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win | OK | Nov 08 2024 |
R-4.5-linux | OK | Nov 08 2024 |
R-4.4-win | OK | Nov 08 2024 |
R-4.4-mac | OK | Nov 08 2024 |
R-4.3-win | OK | Nov 08 2024 |
R-4.3-mac | OK | Nov 08 2024 |
Exports:AsymmdM1dMAFrobeniusLELeigLelwMAEMSEStatPerMeasStein
Dependencies: