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For our probabilistic model, inference becomes slower as the amount of data increases.
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Third, if high values are chosen as limits, the search space of the model inference process becomes very large, adding unnecessary computational load to the already complex reverse-engineering process.
As investigators make subjective changes to the model to avoid these issues, the robustness of the inference becomes increasingly suspect.
The models themselves have been of less significance for understanding system behavior than as a mathematical context in which statistical inference becomes feasible.
As we can see, the inference becomes better as the threshold T0 increases.
In practice, however, inference becomes much more complicated.
Thus, when data is available for the system under study, parameter inference becomes an interesting strategy.
As data sets grow and models for phylogenetic inference become more realistic, it will be necessary to revisit the issue of within-gene LGT.
Consequently, phylogeny inference became one of most standard tasks in evolutionary pipelines.
For the HCRF model, the inference problem becomes intractable because of the dependence structure of the graphical model.
Denied this information about Mars' core, the inferences become more tenuous and model dependent, but comparison with Earth suggests the level of detail that will emerge once Mars is studied seismologically.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com