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Because of the uncertainty of which team would advance from the wildcard matches, I had to run this simulation once for each of the four teams in case it would make a difference. All of these results are from a 10 6 run Monte Carlo simulation, using head-to-head data between the teams and their Elo scores both point-values and moving averages. Not like I just took what they told us they already did and then suggested they added more weights and run multiple simulations with different permutations so we could see which factors favor which teams.
Thanks for your completely useless insight though. I didn't and still dont see any 'suggestions' of any merit in your post. Thanks for the completely useless contribution though. I'm sorry you're struck a learning disability that only lets you read about 5 words per paragraph though.
The only anomaly in this study is that Arrow has barely or has not at all played any of the teams at TI other than Titan which is producing the anomalous result. Dismissing the what the data says about Alliance or Empire absent evidence demonstrates small thinking. The fuck are you on about. You say "how you feel" like everyone in this thread are saying the stats are non-predictive because they think Notail is cuter than Pajkatt so Fnatic should be placed higher than Mousesports.
If you run with a flawed system, e. Stats aren't automatically right because they're stats. Many people in this thread are calling the stats bad because they've watched dota and saw big incongruities between their own qualitative analysis and the statistic quantitative analysis.
Now, everyone who's saying you shouldn't immediately dismiss stats because you don't immediately agree is definitely correct. You should look at the evidence presented and then make a judgement on whether the stats are useful, or in this case, predictive. Which is why I listed multiple examples that are absurd.
This is not mentioning a few red flags that immediately go up when you read their stats. If you've ever seen those simulations for basketball, baseball, or football done by professionals you would know how absolutely ludicrous that is. Also, to put it into perspective, a monte carlo for the digits of pi only gives you 2 significant digits with 10 6 runs.
You can't even get 3. No, it does not mean one million is too few for every monte carlo program, but when half of your teams can't win at all it's a pretty big hint you're doing it wrong. Just as you should not immediately reject stats because you don't agree, you also shouldn't automatically accept stats as sound just because someone ran some simulations with an extremely glossed over methodology overview. Now, non-predicative stats doesn't automatically equal trash or bad stats, that's definitely true.
However, seeing as their title is "The International 4 Predictions" in this case non-predictive most definitely equals bad or useless. And, again, I never claimed their entire list is flawed.
As for why I think their methodology might be flawed instead of everyone's qualitative analysis is wrong is because of everything I've already mentioned but I guess I'll write it again because you're unable to read. These are facts, not feelings. VG -- which you seem to defend staunchly while ignoring or dismissing all other evidence with that flair while accusing everyone else of being biased -- was most definitely the strongest team in the world at ESL One when they came to the west and beat everyone.
It's not I "feel" they're slipping, it's they're slipping. To make it clear, I don't think they're bad, I know they're in decline because all the facts say they are. As for LGD, since they've finally sorted out their roster their head-to-head with VG and overall winrate has improved dramatically within the last 2 and halfish months, both of these things are also facts not because I "feel" LGD has a sexy logo and I don't care for VG's, it's because evidence points to a huge incongruity between reality and results, most specifically results that are much more recent than their arbitrary 6 months.
VG is 18x more likely to enter top 4 and Mousesports, which fact hasn't ever been top 3 in a Lan ever, has almost a 12x chance than LGD. However, for their recent results they did not even qualify for 3 different qualifiers technically 2 since they didn't play summit, but esl frankfurt and WPC were very big and took up most of June the tourney month and only beat 1 team in recent memory and that's Mouz. For them to be ranked above Alliance again isn't because I "feel" like Alliance is the better team, it's because Alliance has qualified for everything in recent months and has placed way higher than Empire quantitative results.
As for your next point, it's completely inane. It's as silly as the argument "if you think X pro player is so bad why don't you join their team and play better then? This is a discussion thread on the statistics used in an article titled "The International 4 Predictions" and I think there's major concerns on their methodology which might make their list non-predictive outside of the top 4 teams.
The most worrisome being their arbitrary time window, weights, and possible no time decay. I would say more about this but I have no idea what they did because they didn't explain it, which is why I suggest more simulations to try and uncover more information. While there's no correct way to arbitrarily do something, i. As for scope and experimenting in general, the first thing everyone asks for is possibility for future research.
I'm not demanding anything, I just think those stats would be interesting. It was a suggestion if they want to come back to the subject. I bring up Nate Silver because he's famous for predictive stats whether deserved or not is up for debate and because he does a great job at managing free variables and explaining the methodology behind how he handled them and why out of the many simulations he's run he's picked a specific one as the most valid.
And your last point is ignorance. You should never take statistics at face value, I think everyone knows that. While I don't think for 1 second they are trying to deceive us into thinking Empire or Arrow is better than everyone else so we lose rares on d2lounge and they can rake in mythicals, at the same time accepting conclusions to the word without questioning all the different things that can go wrong or asking what would happen if they changed their weights on factors for example, with a lower window Fnatic might be higher, a even smaller window might have Alliance higher and then compare results to reach what I believe are much more interesting conclusions is completely silly.
You keep saying no one has evidence on how they feel. Unlike you, who believes stats must be believed unless you run your own simulation with similar complexity.
Just because they didn't make a glaring mistake, like run a monte carlo with only 10 iterations, a mistake I'm sure even you can recognize, doesn't mean their stats are by default good stats. Indeed, there's plenty of stuff in the data that is very different from what I personally believe to be true when TI starts. I was just talking about the specific comment about Arrow above.
Titan has won like most of it's matchup against Arrow and You're asking me questions and using the second person in your reply to me as if I'm one of the people involved in the exercise. I had nothing to do with it. Yeah, what am I actually reading here? Last year's winners, Alliance, barely qualify as even technically having a chance? Just what kind of math happened here Well, if you read the article, the method used is pretty comprehensively explained.
Obviously no statistical analysis of this sort can actually predict the future but the best way to attempt to do so is based on the recent performances of the teams, especially against one another. What you're asking for is basically some kind of rule that says 'no matter how well a team is doing recently, because they won the tournament before they should just have good odds IMPOSED on them.
As I said in the article, there are MANY reasons for teams values being overstated or understated, and this obviously affects all the key variables. The three key ones are. At the end of the day, this is a statistical analysis using a method which has worked historically. The results aren't foolproof, and a lot of the games especially a team like Arrow are game predicted with low confidence values. Does this simulation actually simulation provide you with the confidence values for the results?
And if so, which of the outcomes are statistically significant? Navi Fanboys who don't read the article and only look at the outputs then rage because their favorite team sucks.
Why are you acting like it makes more sense if you actually read the article? It's just as stupid. Ok folks, rule 1 of monte carlo simulations. That's fucking common sense. C9 wins TI4 in about out of the 1 runs. Well that make sense. You should really write that if that's what you mean though. Probably implying that Liquid won't make it through wildcards. However, I think it will be VP versus Liquid in the finals for wildcard.
I'm sorry but what is your simulation methodology? What are your weighting and distrubutions in your Monetcarlo MC? Running 10 6 games per team and it only taking 16 minutes is telling me you are using a ludicriously simple model. It doesn't matter how many runs you do if your MC model is not factoring in necessary factors for instance: Also factor in that chinese teams predominantly been facing chinese team, same for Western: What are your validation methods? Have you run your MC against known outcome tournaments i.
Coming from doing a Particle Physics PhD here using MC data all the time, just because you run an MC doesn't mean your results automatically become more correct. Match the bet, fold or double to see your opponent's hand.
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