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:Carlos Trucios

StatPerMeCo_0.1.0.tar.gz
StatPerMeCo_0.1.0.zip(r-4.7)StatPerMeCo_0.1.0.zip(r-4.6)StatPerMeCo_0.1.0.zip(r-4.5)
StatPerMeCo_0.1.0.tgz(r-4.6-any)StatPerMeCo_0.1.0.tgz(r-4.5-any)
StatPerMeCo_0.1.0.tar.gz(r-4.7-any)StatPerMeCo_0.1.0.tar.gz(r-4.6-any)
StatPerMeCo_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
StatPerMeCo/json (API)

# Install 'StatPerMeCo' in R:
install.packages('StatPerMeCo', repos = c('https://ctruciosm.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.46 score 1 stars 29 scripts 144 downloads 11 exports 0 dependencies

Last updated from:e8735fa477. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK102
source / vignettesOK137
linux-release-x86_64OK88
macos-release-arm64OK93
macos-oldrel-arm64OK87
windows-develOK60
windows-releaseOK108
windows-oldrelOK76
wasm-releaseOK86

Exports:AsymmdM1dMAFrobeniusLELeigLelwMAEMSEStatPerMeasStein

Dependencies: