MRS {MBC} | R Documentation |
Multivariate linear rescaling using Cholesky decomposition
Description
Multivariate linear bias correction based on Cholesky decomposition of the covariance matrix following Scheuer and Stoller (1962) and Bürger et al. (2011). Bias correction matches the multivariate mean and covariance structure.
Usage
MRS(o.c, m.c, m.p, o.c.chol=NULL, o.p.chol=NULL, m.c.chol=NULL,
m.p.chol=NULL)
Arguments
o.c |
matrix of observed samples during the calibration period. |
m.c |
matrix of model outputs during the calibration period. |
m.p |
matrix of model outputs during the projected period. |
o.c.chol |
precalculated Cholesky decomposition of the |
o.p.chol |
precalculated Cholesky decomposition of the target |
m.c.chol |
precalculated Cholesky decomposition of the |
m.p.chol |
precalculated Cholesky decomposition of the |
Value
a list of with elements consisting of:
mhat.c |
matrix of bias corrected |
mhat.p |
matrix of bias corrected |
References
Scheuer, E.M. and D.S. Stoller, 1962. On the generation of normal random vectors. Technometrics, 4(2):278-281.
Bürger, G., J. Schulla, and A.T. Werner, 2011. Estimates of future flow, including extremes, of the Columbia River headwaters. Water Resources Research, 47(10):W10520. doi:10.1029/2010WR009716