NMOF (version 2.2-2)

resampleC: Resample with Specified Rank Correlation

Description

Resample with replacement from a number of vectors; the sample will have a specified rank correlation.

Usage

resampleC(..., size, cormat)

Arguments

…

numeric vectors; they need not have the same length.

size

an integer: the number of samples to draw

cormat

the rank correlation matrix

Value

a numeric matrix with size rows. The columns contain the samples; hence, there will be as many columns as vectors passed through ….

Details

See Gilli, Maringer and Schumann (2011), Section 7.1.2. The function samples with replacement from the vectors passed through …. The resulting samples will have an (approximate) rank correlation as specified in cormat.

The function uses the eigenvalue decomposition to generate the correlation; it will not break down in case of a semidefinite matrix. If an eigenvalue of cormat is smaller than zero, a warning is issued (but the function proceeds).

References

Gilli, M., Maringer, D. and Schumann, E. (2019) Numerical Methods and Optimization in Finance. 2nd edition. Elsevier. https://www.elsevier.com/books/numerical-methods-and-optimization-in-finance/gilli/978-0-12-815065-8

Schumann, E. (2019) Financial Optimisation with R (NMOF Manual). http://enricoschumann.net/NMOF.htm#NMOFmanual

See Also

repairMatrix

Examples

# NOT RUN {
## a sample
v1 <- rnorm(20)
v2 <- runif(50)
v3 <- rbinom(100, size = 50, prob = 0.4)

## a correlation matrix
cormat <- array(0.5, dim = c(3, 3))
diag(cormat) <- 1

cor(resampleC(a = v1, b = v2, v3, size = 100, cormat = cormat),
    method = "spearman")
# }