Recent content by Dason

1. weighting votes calculation

Well it sounds like you should do that. What issues are you having
2. HELP

Show your output. We want to help but you rarely show what you're referring to until we explicitly ask.
3. One-Sample Bayesian Proportion Test

When comparing a histogram to a density plot you need to use probability=TRUE in the histogram. Since you know the exact distractions for the prior and posterior you don't need to use rbeta - use dbeta directly.
4. HELP

Use plot with the data directly. Like plot(x,y) and then call abline
5. HELP

Of course it showed a different number. That's like the entire reason we need statistics.

7. One-Sample Bayesian Proportion Test

https://en.wikipedia.org/wiki/Conjugate_prior#Example
8. One-Sample Bayesian Proportion Test

Yes. It is that simple. Conjugate priors are nice.
9. Producing Win Probabilities for Professional Tennis Matches from any Score

If you pull out a specific line of code tell us where it is located. I don't want to read the whole paper.
10. Producing Win Probabilities for Professional Tennis Matches from any Score

I think we need more context for your specific questions. Pulling a single line out of an algorithm isn't entirely useful to us.
11. One-Sample Bayesian Proportion Test

I didn't check completely but the beta distribution is a conjugate prior for a binomial distribution which really reduces the complexity so the posterior distribution is able to be derived analytically (and is another beta). We really only 'need' mcmc when we can't analytically derive the...
12. Distribution evaluation problem - Updated

Do you know what n is each time. And do you have a functional form for that density?
13. Distribution evaluation problem - Updated

Do you know anything else about the distribution? Maybe some functional form for probability mass function? Is n known?
14. Distribution evaluation problem - Updated

I'll be honest. I don't think you did a good job describing your problem in a way that others can follow. Can you give it another go? Also are you sure you meant left skewed? Right skewed for what you were describing would make much more sense to me...
15. Confidence interval - why not porbability

What exactly would you mean by "true confidence interval"?