@@ -36,7 +36,18 @@ The above plot shows the array of the eigenvalues. This plot indicates that the
# Choice of the rank of the covariance matrix
## GW190814
First, we demonstrate an example from the GW190814 event to find an appropriate cut-off on the low-rank approximation of the covariance matrix, and its effect on $`\beta`$. We choose top 5 PE samples and plot $`\beta`$ as a function of the rank of the covariance matrix. The spectrum of the eigenvalues is also plotted.
First, we demonstrate an example from the GW190814 event to find an appropriate cut-off on the low-rank approximation of the covariance matrix, and its effect on $`\beta`$. We choose top 5 [PE samples](https://ldas-jobs.ligo.caltech.edu/~charlie.hoy/PE/O3/S190814bv/C01/SEOBNRv4HM/samples/SEOBNRv4HM_pesummary.dat)(largest likelihood values ) and plot $`\beta`$ as a function of the rank of the covariance matrix.
