Recent content by lalekl

the inability of users to figure out a question is not grounds for closing a thread especially while people are still answering. on top of it, the moderators are needlessly rude. just juvenile and not held to the same standards they demand on people asking questions.

Thank you, between this and some of the inequalities I've mentioned before, I have a complete solution to the above problem. I will program it up and see how fast it converges.

Very interesting! So much to learn and explore here. I think I am missing something to get ##S_n## and ##E[J]## increase linearly together. I see ##E[J]## has to increase linearly with ##E[Y_1...+Y_J]##. So does that rely on ##E[Y_1...+Y_J]## and ##S_n## increasing linearly together, and is...

Sorry to mislead with the non-sequitor...I didn't think it was, I just don't think estimating ##E[J]## is practical but I think other methods are and empirically they converge faster but I need a strong statement to make progress on them... the question in the other thread was meant to be more...

Camilla plays a casino game with fixed bet, fixed odds, no skill, and a starting bankroll, ##M_0##. She plays until she can no longer afford to bet and records in a journal only her bankroll and how many bets she was able to make, ##N_0##, until she could not afford to bet. She has amnesia...

Listen for any practical real application, your method “works”; but it misses part of the spirit of the problem which is to not have a different method depending on what kind of distributions you think you might be getting from the very limited information set. The game still has disrcrete...

Yeah i like that...I also got complaints i think for using “runs out of money” though, so rewrote as “can no longer afford to bet” or something like that...although i will have to say you can say a player knows that there are inifinite possibilities on s slot machine but it is stretching it to...

Now we’re cooking with whale oil! But how?

Yes I agree, I think I am having the same issue with your solution as I am with andrewkirk's: a paytable consisting of every pay and a fixed probability for that pay requires you to estimate the number of parameters in the set up. But since she doesn't know those she has to find all possible...

Either way, the point is she is ignorant of how many possible parameters there are to estimate, can you guarantee that your estimation method doesn't demand more parameters than there is data?

i updated the wording to be less confusing in that respect

it means the odds of any given pay do not change day to day, but the player is ignorant of the paytable.

the unknown distribution could pay out any non-negative number as far as the player is concerned

the support of the game is unbounded, should i treat an infinite vector of the odds as one parameter? that doesn't seem to work for me...

sorry i read your response too quickly. I'm still having an issue where if we don't know the distribution, how can we construct this likelihood function? It seems to me that the number of parameters grows faster than the observations...that's a problem isn't it?