The stochastic model implemented here will be used for validating the counting algorithms designed in the next sections.
The model implemented here defines an error to be the replacement of the true genotype at a particular locus in an individual with a random genotype.
Some important remarks concerning the statistical approach deserve to be highlighted: the model implemented here showed a good fit, despite the fact there was little information to update the prior distributions.
The Mkv model implemented here can potentially account for convergent changes, but only when the data include the single-taxon changes (or autapomorphies) that characterize long branches and can help identify adaptive convergent evolution (Lewis, 2001).
An important future direction for this work is to implement the multiple-threshold version of the model proposed by Monaghan et al. [ 28], which can account for greater variation in divergence times and effective population sizes than the model implemented here.
However, in the BayesB model implemented here, the prior distribution assumed that the majority of the markers (i.e. the fraction 1- NQTL/Nm) did have a small effect, the variance of which was assumed equal and was estimated in the model, instead of assuming that these markers had no effect at all (as in [ 2]).
In the model implemented here, it is assumed that all hypnozoites in an infection must undergo some waiting period before any of them can activate, and that during the long-latency phase hypnozoites are at risk of death due to natural hepatocyte death.
Comparing the single-level MIQP model, OptMod, to the reduced MIQP models as implemented here, the latter strategy involves fewer variables and constraints and can be terminated efficiently even in cases of larger size networks, as discussed in the Results and Discussion section.
This section first describes the formulation of the DEA models as implemented here for the measurement of container port efficiency.
