# resampleC: Resample with Specified Rank Correlation In NMOF: Numerical Methods and Optimization in Finance

## Description

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

## Usage

 `1` ```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

## 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).

## Value

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

Enrico Schumann

## References

Gilli, M., Maringer, D. and Schumann, E. (2011) Numerical Methods and Optimization in Finance. Elsevier. http://www.elsevierdirect.com/product.jsp?isbn=9780123756626

Schumann, E. (2016) Financial Optimisation with R (NMOF Manual). http://enricoschumann.net/NMOF.htm#NMOFmanual

`repairMatrix`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## 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") ```