Quote:
Originally Posted by Dawis
Hi all.
..
1. This is not an attempt to offer real loot function underneath the EU, this is simply statistical research of results this function gives - thus real loot we get over time. Which is ok - you can`t prove any reasonable theory about loot function anyways - so lets just analyze what is coming out of the black box. |
that's correct and I stated this in the text. Nevertheless, there will still be one confusing it.
Quote:
Originally Posted by Dawis
2. It is a bit difficult to get large samples of data even for results of this black box - loot we get. Each avatar can only get full data about his own results - and even that is not easy - so more acurate data we want - more difficult it is to get in large enough samples.
We can escape this problem, by reading only globals that appear into the system - because system offers a nice way to get access to data about all loots above 50 ped. (big respect to person for building the http://87.62.217.174/login.asp system which allows everyone to access this data easy)
As I understand author of this thread uses results of this system for building his theory. |
indeed, and for an exp dist you need quite some data to get all aspects. It would be easier with a normal dist.
Quote:
Originally Posted by Dawis
...
One easy way to do this is assume Loot = health * C(x) where C is constant generated at event x by our black box of loot function which inner workings is not our concern.
This provides us with easy solution of only measuring Loot / health not plain loot.(we assume loot proportionaly increases by increasing monsters health)
Thus by measuring Loot/health we measure how good is loot with respect to monster we are hunting.
As I said I did not have time to understand all maths behind authors theory, but I believe author has taken health into account correctly.
|
thats a good approach and one can analyze loot that is health corrected. However, you loose the possibility to model health, since you corrected for it. I did this analysis in the beginning to understand what kind of dist we have.
Quote:
Originally Posted by Dawis
1. Although there is strong corelation between monsters health and size of it`s loot we loose much of this corelation if we look only at globals we get from this monster. Why?
Simply: If monster monster A has 200 health and monster B has 2000 health it does not mean that every global you get from monster B will be 10 times as big. Not even close, becasue you will get a lot small globals from B, as oposed to only rare globals from A.
This raises a problem, because current method uses data we get from globals. Only possible solution I currently see is - increase minimum global date we take into account from monster B proportionaly.
Let me explain:
1. Killing 1000 monster A you will probably get 2 globals
2. Killing 1000 monster B you will probably get 20 globals
Of course you will get lots of small globals from B - because loot proportionaly increases with size of monster hp. So to save corelation between monsters health and monster loot in B case we look only at the globals which exceed 500 PED.
Math nehind this is easy:
Monster A health 200
Monster B health 2000
Ratio = 10
Assumption - loot should be 10x greater from B
We cant get acces to all loot date - we get only global data. So minimum loot we see is 50 ped.
In A case this means we measure only the best loots from A monster (pikes of loot function).
In B case this means we measure not only the best but medicore loots to.
To compensate this we multiply minimum measurement requirement by 10 in B case. So we get aproximately even amount of data samples in both cases.
Ok.. I am exausted for now  |
fortunately a truncated exp will have the same characteritics as one that is not truncated. The only difference is the different mean you'll get. If you know the truncation point the original mean is estimated mean - truncation point. However, it is also possible that globals start at 50.
In analyzing globals you won't get any information on normal loot. We had some threads about that before and both results should be finally combined.
I used the Cos model to test for health on loot. The advantage with this model is, that you don't have to know the real distribution.
You'r porposal to analyze only loot higher than some threshold is dangerous. As outlined before, we do observe a mixture of several distributions. Therefore in using a threshold you'll hardly know what kind of data you have. You have to know one of the distributions to find a good threshold.