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A deliberately incomplete view of the literature, as I hope I've explained, isn't a neutral or marginal failure.
In what follows, we will build a bivariate distribution with increasing marginal failure rates.
The building scheme may be relaxed under additional available information regarding monotone behavior of marginal failure rates.
In fact, the class of bivariate distributions (mathcal {L}(mathbf {x};mathbf {a})) may have arbitrary combination of marginal failure rates: increasing, decreasing, constant, bathtub, etc., implying corresponding restrictions for the parameter space, of course.
The next two examples illustrate how relations in Theorem 4 can be applied to construct bivariate distributions from (mathcal {L}(mathbf {x};mathbf {a})) with given marginal failure rates.
The next result offers another set of equivalent constraints for parameters of (mathcal {L}(mathbf {x};mathbf {a})), but in terms of marginal failure rates (r_{X_{i}}(x), ; i = 1,2).
Similar(49)
Let's stop undermining our own efforts, broadcasting our marginal failures.
One theoretical concern regarding the improved tissue sparing offered by IMRT is a potential increase in marginal failures, but marginal failures were not observed in this study population.
The risk of marginal failures may be reduced by increasing the precision of treatment using an adequate and very tight dose coverage of target volumes.
IMRT with IGRT could theoretically improve local control in T4N0 disease by reducing the incidence of marginal failures, and this hypothesis should be tested in the clinic.
Therefore, the current analysis allows us to conclude that FSRT can be applied in patients with EP without an increased risk for marginal failures.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com