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Compute the BAHC covariance matrix.
filterCovariance(x, k = 1, Nboot = 100)
A matrix: \(x_{i,f}\) is feature \(f\) of object \(i\)
The order of filtering. \(k=1\) corresponds to BAHC.
The number of bootstrap copies
The BAHC-filtered correlation matrix of x.
x
# NOT RUN { r=matrix(rnorm(1000),nrow=20) # 20 objects, 50 features each sigma=exp(runif(20)) rs=t(sigma %*% r) %*% sigma Cov_bahc=filterCovariance(rs) # }
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