Search Results

I cannot comment due to rep requirements but Alekk's comment reg weight- If you use hierarchical bayesian (also known as multi-level models) ideas to process the data then the observations coming from …

I am not entirely sure what you are asking but ... The model you reference in the wiki article has a memory-less distribution for waiting time and inter-arrival time. Thus, the total time for a reque …

You should use hierarchical bayesian regression. Google search will provide lots of pointers.

Context Consider the following sequential data generating process for $Y_1$, $Y_2$, $Y_3$. (By sequential I mean that we generate $Y_1$, $Y_2$, $Y_3$ in sequence.): $Y_1 = X_1^' \beta + \epsilon_1$ …

Suppose you perform 2 draws and observe the sequence {v1, 0}. Then your question is: P( {v1, 0} | m ) = ?. The intuitive way to think of P( {v1, 0} | m ) is the take the frequentist perspective an …

This is how I would approach the problem: Let $\theta_{ij}$ be the probability that i beats j and let $w_{ij}$ be the number of times i wins over j in $n_{ij}$ trials. Then, the likelihood function i …

Now that I understand your question better, here is another attempt: Let $S_i$ be how strong item i is intrinsically. In a competition between items i and j the probability of i winning will depend o …

Another perspective that may help here comes from Bayesian statistics. You can model the outcome of competition between any two players using an unknown strength variable (say , $S_i$ ). Then, define: …

Use the inverse transform method.

I think Mathematica or a suitable CAS is the way to go to deal with this issue.