| Type: | Package |
| Title: | Filter Covariance and Correlation Matrices with Bootstrapped-Averaged Hierarchical Ansatz |
| Version: | 0.3.0 |
| Date: | 2020-09-21 |
| Author: | Christian Bongiorno and Damien Challet |
| Maintainer: | Damien Challet <damien.challet@gmail.com> |
| Description: | A method to filter correlation and covariance matrices by averaging bootstrapped filtered hierarchical clustering and boosting. See Ch. Bongiorno and D. Challet, Covariance matrix filtering with bootstrapped hierarchies (2020) <doi:10.48550/arXiv.2003.05807> and Ch. Bongiorno and D. Challet, Reactive Global Minimum Variance Portfolios with k-BAHC covariance cleaning (2020) <doi:10.48550/arXiv.2005.08703>. |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| Depends: | R (≥ 3.5.0), fastcluster, matrixStats |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.0 |
| NeedsCompilation: | no |
| Packaged: | 2020-09-21 15:57:33 UTC; damien |
| Repository: | CRAN |
| Date/Publication: | 2020-09-21 16:40:02 UTC |
Compute the BAHC correlation matrix.
Description
Compute the BAHC correlation matrix.
Usage
filterCorrelation(x, k = 1, Nboot = 100)
Arguments
x |
A matrix: |
k |
The order of filtering. |
Nboot |
The number of bootstrap copies |
Value
The BAHC-filtered correlation matrix of x.
Examples
r=matrix(rnorm(1000),nrow=20) # 20 objects, 50 features each
Cor_bahc=filterCorrelation(r)
Compute the BAHC covariance matrix.
Description
Compute the BAHC covariance matrix.
Usage
filterCovariance(x, k = 1, Nboot = 100)
Arguments
x |
A matrix: |
k |
The order of filtering. |
Nboot |
The number of bootstrap copies |
Value
The BAHC-filtered correlation matrix of x.
Examples
r=matrix(rnorm(1000),nrow=20) # 20 objects, 50 features each
sigma=exp(runif(20))
rs=t(sigma %*% r) %*% sigma
Cov_bahc=filterCovariance(rs)