LE: Euclidean distance

In StatPerMeCo: Statistical Performance Measures to Evaluate Covariance Matrix Estimates

Description

Compute the Euclidean distance between the matrices S and H. See, Laurent et al. (2012) and Amendola et al. (2015).

Usage

LE(S, H)

Arguments

S	Proxy for the conditional covariance/correlation matrix
H	Estimate of the conditional covariance/correlation matrix.

Author(s)

Carlos Trucios

References

Amendola, A., & Storti, G. (2015). Model uncertainty and forecast combination in high-dimensional multivariate volatility prediction. Journal of Forecasting, 34(2), 83-91.

Laurent, S., Rombouts, J. V., & Violante, F. (2012). On the forecasting accuracy of multivariate GARCH models. Journal of Applied Econometrics, 27(6), 934-955.

Examples

X = matrix(rnorm(4000),ncol=4)
S = diag(4)
H = cov(X)

LE(S, H)

Example output

[1] 0.03305074

StatPerMeCo documentation built on May 2, 2019, 12:21 p.m.