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Ries offers that it could be advantageous for investors to make smaller, more consistent investments versus offering fewer, larger rounds but notes the problem to this approach is "we don't currently have any objective data about who is making progress and who is not".
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There are some benefits, and a few problems to this approach vs. those taken by GamePop competitors.
The main problem related to this approach was the unavailability of specific databases of events.
As we will show, one problem associated to this approach is that it does not account for the uncertainty present in the input.
Several researchers have noted the problems related to this approach.
To correct for the multiple hypothesis tests problems inherent to this approach, we judged results to be significant allowing a maximum false discovery rate (FDR) of 20% [ 96, 98].
Recent advances in scientific computing, however, allow this problem to be approached from a new perspective.
So what is the problem with this approach to building a city from the ground up?
There are several interconnected issues to this problem and this approach.
We call the optimization problem in this approach to supertree estimation "matrix representation with likelihood", or MRL.
However, we have already alluded to problems with this approach (§3.3).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com