Assume a friend has developed an excellent program for finding the steady-state probabilities for finite-state Markov chains. More precisely, given the tran- sition matrix [P], the program returns lim...


Assume a friend has developed an excellent program for finding the steady-state probabilities for finite-state Markov chains. More precisely, given the tran- sition matrix [P], the program returns limn P
n
for each
i. Assume all chains are aperiodic.



(a)
You want to find the expected time to first reach a given state
k
starting from a different state
m
for a Markov chain with transition matrix [P]. You modify the matrix





















km



to [P∗] where
P




= 1,
P




= 0 for
j

/=
m, and
P




=
P
ij
otherwise. How do you find





















kj


















ij



the desired first-passage time from the program output given [P∗] as an input? Hint: The


times at which a Markov chain enters any given state can be considered as renewals in a (perhaps delayed) renewal process.



(b)
Using the same [P∗] as the program input, how can you find the expected number


of returns to state
m
before the first passage to state
k?



(c)
Suppose, for the same Markov chain [P] and the same starting state
m, you want to find the probability of reaching some given state
n

before the first passage to
k. Modify [P] to some [P∗∗] so that the above program with
P∗∗ as an input allows you to easily find the desired probability.



(d)
Let Pr{X(0) =
i} =
Q
i, 1  ≤
i
≤ M be an arbitrary set of initial probabilities for the same Markov chain [P] as above. Show how to modify [P] to some [P∗∗∗] for which the steady-state probabilities allow you to easily find the expected time of the first passage to state
k.


May 12, 2022
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