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Calibrating information can be incorporated into an analysis in one of several ways [15], of which the most widely used are: (i) fixing the age of a phylogenetic divergence event on the basis of independent palaeontological, archaeological, or biogeographic data; and (ii) importing a substitution rate obtained from independent data.
We solve the blind deconvolution problem using an iterative procedure: (i) fixing k and estimating latent signal X using a specific non-blind deconvolution method based on iterative support detection (ISD) (described below) and then (ii) fixing X to estimate convolution kernel k to correct for cross-talk and phasing effects.
Algorithms to solve this optimization problem involve iterating over two steps: (i) fixing Θ and minimizing the objective function with respect to X (hence falling back to solve MDS2) and (ii) fitting Θ to the new configuration X subject to the ordinal constraints.
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