TL-DR
Our analysis wanted to answer two simple (sort of) questions:
1- Is the PIP-22 / PUP-21 model being fair with nodes (regardless their QoS)? Or, Are my rewards the same as before (regardless my QoS)?
2- Is modeling the Cherry Picker as linear correct? Or, do an increase in sessions by node of X% translates into an increase of relays of X%?
The analysis provided by @msa6867 do not address neither of this questions.
To answer the first question, he focuses on using a macro view of the Pocket Network, ignoring division of QoS in their analysis. Instead of analyzing node runners grouped by their QoS, he merges all nodes into a single group. This is what he call “weighted average”. This is the same as taking a group of N random nodes from the network and adding them all as a single entity. It is evident that this metric is not addressing a problem of fairness within different node runners. Also, by doing so he achieves a trivial and expected result that the number of relays by node stays constant. No surprise here, the Pocket Network is a closed system, the relays need to go somewhere, he only proved that the sub-set of node runners used in our analysis is correct. Finally he uses this value as the basis of his thesis showing that there is no fairness issue, but it is only a single metric, how can a single metric give us any insight on how the metric changed in two groups of node runners (low and high-QoS)?
The second question is completely ignored with some weak critic over the statistical metric that was proposed. This is very worrying as dismissing such metric requires giving proof that is not applicable. Also, he asks us to apply it on other segments of time, knowing (I hope) that it will shield very different results. This is expected, if you do not expect to see a strong change in one of the variables (number of sessions by node in this case) you will be measuring noise. There is not an other time period where the number of nodes was reduced so largely, the time frame chosen to apply this metric is the best one in the history of the Pocket Network.
Finally, ignoring the statistical proofs that show that modeling the cherry picker with a linear model is not correct, he uses a linear model in all its “justifications”. This means that all the examples that he presents are not valid since they are based in a false premise.