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do we want to absorb \sigma_m^2 term in the covariance matrix as was done at the end of appendix B, or do we want m to be a free parameter with a Gaussian prior with a variance of \sigma_m^2
do we want to absorb \sigma_m^2 term in the covariance matrix as was done at the end of appendix B, or do we want m to be a free parameter with a Gaussian prior with a variance of \sigma_m^2