Proving Martingale Property and Stopping Theorem for Probability Homework

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SUMMARY

The discussion focuses on proving the martingale property of a sequence defined as Z_n = X_n / (n + 2), where X_n represents the number of white balls in an urn after n replications. The key steps involve calculating the expected value E[Z_{n+1} | Z_1, Z_2, ..., Z_n] and demonstrating that it equals Z_n, thus confirming the martingale property. Additionally, the conversation addresses the application of the martingale stopping theorem to derive E[1/(T + 2)] - 1/4, where T is the first stage at which a black ball is drawn.

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  • Understanding of martingale theory in probability
  • Familiarity with conditional expectation
  • Knowledge of probability distributions related to urn models
  • Basic concepts of stopping times in stochastic processes
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To start with, what is the definition of a martingale?
 


e(ho0n3 said:
To start with, what is the definition of a martingale?

Do you know the answer to the question or are you teaching me?

E[ Z_{n+1}| Z_1 ,Z_2,...,Z_n] =Z_n
 


1) After the nth replication, there are Z_n(n+2) white balls and (1-Z_n)(n+2) black balls in the urn.

2) In the (n+1)th replication, there will either be a white ball or a black ball added into the urn. For each of these cases, what will the new proportion of white balls in the urn be and what are the associated probabilities? Use the definition of expectation to calculate E \ [\ Z_{n+1}\ | \ Z_{1} , \ Z_{2} \, ..., \ Z_{n} \ ]
 
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pizzasky said:
1) After the nth replication, there are Z_n(n+2) white balls and (1-Z_n)(n+2) black balls in the urn.

2) In the (n+1)th replication, there will either be a white ball or a black ball added into the urn. For each of these cases, what will the new proportion of white balls in the urn be and what are the associated probabilities? Use the definition of expectation to calculate E \ [\ Z_{n+1}\ | \ Z_{1} , \ Z_{2} \, ..., \ Z_{n} \ ]

I thought that at each replication two white balls are added or removed. But suppose you're right then I get:

Z_{n+1}= \frac{Z_n(n+2)+1}{n+3}

Z_{n+1} = \frac{Z_n(n+2)-1}{n+3}

with probabilities 1/2 for each?
 


At each replication, a ball is drawn from the urn. The colour of the ball is noted, then that ball, together with a new ball of the same colour, are placed into the urn. Note then that after each replication, the number of white balls in the urn either stays the same or increases by one.

Now, what is the probability of drawing a white ball (similarly, a black ball) from the urn during the (n+1)th replication? (Not necessarily half!)

If a white ball is drawn during the (n+1)th replication, then that white ball will be put back into the urn and a new white ball added. So, what will the proportion of white balls be after the (n+1)th replication? Similarly, if a black ball is drawn during the (n+1)th replication, what will the new proportion of white balls in the urn be?
 
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So

E[Z_{n+1}|Z_1,...,Z_n] = Z_n \cdot \frac{Z_n (n+2) +1}{n+3} +(1-Z_n) \cdot \frac{Z_n (n+2) +1}{n+3} =Z_n

Ok thanks. The next question is:

if T is the first stage at which a black ball is drawn prove that then:E \left[ \frac{1}{T+2} \right] - \frac{1}{4} via the martingale stopping theorem.

http://img45.imageshack.us/img45/2362/85438730sk6.png If X_N is the number of white balls in stage n then:

E[Z_T] = E[Z_1] = \frac{1}{2} = E \left[ \frac{X_T}{T+2} \right] = E[X_T] E \left[ \frac{1}{T+2} \right]

Is this correct?
 
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