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StatPerMeCo  

Statistical Performance Measures to Evaluate Covariance Matrix Estimates
View on CRAN: Click here


Download and install StatPerMeCo package within the R console
Install from CRAN:
install.packages("StatPerMeCo")

Install from Github:
library("remotes")
install_github("cran/StatPerMeCo")

Install by package version:
library("remotes")
install_version("StatPerMeCo", "0.1.0")



Attach the package and use:
library("StatPerMeCo")
Maintained by
Carlos Trucios
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-04-14
Latest Update: 2017-04-14
Description:
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> andBecker et al. (2015) <doi:10.1016/j.ijforecast.2013.11.007>.
How to cite:
Carlos Trucios (2017). StatPerMeCo: Statistical Performance Measures to Evaluate Covariance Matrix Estimates. R package version 0.1.0, https://cran.r-project.org/web/packages/StatPerMeCo. Accessed 21 Nov. 2024.
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Complete documentation for StatPerMeCo
Functions, R codes and Examples using the StatPerMeCo R package
Some associated functions: Asymm . DM1 . DMA . Frobenius . LE . Leig . Lelw . MAE . MSE . StatPerMeas . Stein . 
Some associated R codes: Measures.R . StatPerMeas.R .  Full StatPerMeCo package functions and examples
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